{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Logistic Regression with a Neural Network mindset\n",
    "\n",
    "Welcome to your first (required) programming assignment! You will build a logistic regression classifier to recognize  cats. This assignment will step you through how to do this with a Neural Network mindset, and so will also hone your intuitions about deep learning.\n",
    "\n",
    "**Instructions:**\n",
    "- Do not use loops (for/while) in your code, unless the instructions explicitly ask you to do so.\n",
    "\n",
    "**You will learn to:**\n",
    "- Build the general architecture of a learning algorithm, including:\n",
    "    - Initializing parameters\n",
    "    - Calculating the cost function and its gradient\n",
    "    - Using an optimization algorithm (gradient descent) \n",
    "- Gather all three functions above into a main model function, in the right order."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1 - Packages ##\n",
    "\n",
    "First, let's run the cell below to import all the packages that you will need during this assignment. \n",
    "- [numpy](www.numpy.org) is the fundamental package for scientific computing with Python.\n",
    "- [h5py](http://www.h5py.org) is a common package to interact with a dataset that is stored on an H5 file.\n",
    "- [matplotlib](http://matplotlib.org) is a famous library to plot graphs in Python.\n",
    "- [PIL](http://www.pythonware.com/products/pil/) and [scipy](https://www.scipy.org/) are used here to test your model with your own picture at the end."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n",
      "/opt/conda/lib/python3.5/site-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.\n",
      "  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import h5py\n",
    "import scipy\n",
    "from PIL import Image\n",
    "from scipy import ndimage\n",
    "from lr_utils import load_dataset\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 2 - Overview of the Problem set ##\n",
    "\n",
    "**Problem Statement**: You are given a dataset (\"data.h5\") containing:\n",
    "    - a training set of m_train images labeled as cat (y=1) or non-cat (y=0)\n",
    "    - a test set of m_test images labeled as cat or non-cat\n",
    "    - each image is of shape (num_px, num_px, 3) where 3 is for the 3 channels (RGB). Thus, each image is square (height = num_px) and (width = num_px).\n",
    "\n",
    "You will build a simple image-recognition algorithm that can correctly classify pictures as cat or non-cat.\n",
    "\n",
    "Let's get more familiar with the dataset. Load the data by running the following code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loading the data (cat/non-cat)\n",
    "train_set_x_orig, train_set_y, test_set_x_orig, test_set_y, classes = load_dataset()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We added \"_orig\" at the end of image datasets (train and test) because we are going to preprocess them. After preprocessing, we will end up with train_set_x and test_set_x (the labels train_set_y and test_set_y don't need any preprocessing).\n",
    "\n",
    "Each line of your train_set_x_orig and test_set_x_orig is an array representing an image. You can visualize an example by running the following code. Feel free also to change the `index` value and re-run to see other images. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "y = [1], it's a 'cat' picture.\n"
     ]
    },
    {
     "data": {
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U9YSy3qKcbvUpN2cFvTd34RMWLIwFAKhVkfX0irjrudDHxbEt6gTzH1QMRt+B3kUSoQKi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gAeuC3tT8zVQeaw8mrOqIO7fIiDKX9tRSu4bnL7NpA/K73S7UGwroSVEXZCUdl/6T6GeV8LZA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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f80d99521d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Example of a picture\n",
    "index = 25\n",
    "plt.imshow(train_set_x_orig[index])\n",
    "print (\"y = \" + str(train_set_y[:, index]) + \", it's a '\" + classes[np.squeeze(train_set_y[:, index])].decode(\"utf-8\") +  \"' picture.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Many software bugs in deep learning come from having matrix/vector dimensions that don't fit. If you can keep your matrix/vector dimensions straight you will go a long way toward eliminating many bugs. \n",
    "\n",
    "**Exercise:** Find the values for:\n",
    "    - m_train (number of training examples)\n",
    "    - m_test (number of test examples)\n",
    "    - num_px (= height = width of a training image)\n",
    "Remember that `train_set_x_orig` is a numpy-array of shape (m_train, num_px, num_px, 3). For instance, you can access `m_train` by writing `train_set_x_orig.shape[0]`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of training examples: m_train = 209\n",
      "Number of testing examples: m_test = 50\n",
      "Height/Width of each image: num_px = 64\n",
      "Each image is of size: (64, 64, 3)\n",
      "train_set_x shape: (209, 64, 64, 3)\n",
      "train_set_y shape: (1, 209)\n",
      "test_set_x shape: (50, 64, 64, 3)\n",
      "test_set_y shape: (1, 50)\n"
     ]
    }
   ],
   "source": [
    "### START CODE HERE ### (≈ 3 lines of code)\n",
    "m_train = None\n",
    "m_test = None\n",
    "num_px = None\n",
    "### END CODE HERE ###\n",
    "\n",
    "print (\"Number of training examples: m_train = \" + str(m_train))\n",
    "print (\"Number of testing examples: m_test = \" + str(m_test))\n",
    "print (\"Height/Width of each image: num_px = \" + str(num_px))\n",
    "print (\"Each image is of size: (\" + str(num_px) + \", \" + str(num_px) + \", 3)\")\n",
    "print (\"train_set_x shape: \" + str(train_set_x_orig.shape))\n",
    "print (\"train_set_y shape: \" + str(train_set_y.shape))\n",
    "print (\"test_set_x shape: \" + str(test_set_x_orig.shape))\n",
    "print (\"test_set_y shape: \" + str(test_set_y.shape))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Expected Output for m_train, m_test and num_px**: \n",
    "<table style=\"width:15%\">\n",
    "  <tr>\n",
    "    <td>**m_train**</td>\n",
    "    <td> 209 </td> \n",
    "  </tr>\n",
    "  \n",
    "  <tr>\n",
    "    <td>**m_test**</td>\n",
    "    <td> 50 </td> \n",
    "  </tr>\n",
    "  \n",
    "  <tr>\n",
    "    <td>**num_px**</td>\n",
    "    <td> 64 </td> \n",
    "  </tr>\n",
    "  \n",
    "</table>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For convenience, you should now reshape images of shape (num_px, num_px, 3) in a numpy-array of shape (num_px $*$ num_px $*$ 3, 1). After this, our training (and test) dataset is a numpy-array where each column represents a flattened image. There should be m_train (respectively m_test) columns.\n",
    "\n",
    "**Exercise:** Reshape the training and test data sets so that images of size (num_px, num_px, 3) are flattened into single vectors of shape (num\\_px $*$ num\\_px $*$ 3, 1).\n",
    "\n",
    "A trick when you want to flatten a matrix X of shape (a,b,c,d) to a matrix X_flatten of shape (b$*$c$*$d, a) is to use: \n",
    "```python\n",
    "X_flatten = X.reshape(X.shape[0], -1).T      # X.T is the transpose of X\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_set_x_flatten shape: (12288, 209)\n",
      "train_set_y shape: (1, 209)\n",
      "test_set_x_flatten shape: (12288, 50)\n",
      "test_set_y shape: (1, 50)\n",
      "sanity check after reshaping: [17 31 56 22 33]\n"
     ]
    }
   ],
   "source": [
    "# Reshape the training and test examples\n",
    "\n",
    "### START CODE HERE ### (≈ 2 lines of code)\n",
    "train_set_x_flatten = None\n",
    "test_set_x_flatten = None\n",
    "### END CODE HERE ###\n",
    "\n",
    "print (\"train_set_x_flatten shape: \" + str(train_set_x_flatten.shape))\n",
    "print (\"train_set_y shape: \" + str(train_set_y.shape))\n",
    "print (\"test_set_x_flatten shape: \" + str(test_set_x_flatten.shape))\n",
    "print (\"test_set_y shape: \" + str(test_set_y.shape))\n",
    "print (\"sanity check after reshaping: \" + str(train_set_x_flatten[0:5,0]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Expected Output**: \n",
    "\n",
    "<table style=\"width:35%\">\n",
    "  <tr>\n",
    "    <td>**train_set_x_flatten shape**</td>\n",
    "    <td> (12288, 209)</td> \n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>**train_set_y shape**</td>\n",
    "    <td>(1, 209)</td> \n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>**test_set_x_flatten shape**</td>\n",
    "    <td>(12288, 50)</td> \n",
    "  </tr>\n",
    "  <tr>\n",
    "    <td>**test_set_y shape**</td>\n",
    "    <td>(1, 50)</td> \n",
    "  </tr>\n",
    "  <tr>\n",
    "  <td>**sanity check after reshaping**</td>\n",
    "  <td>[17 31 56 22 33]</td> \n",
    "  </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To represent color images, the red, green and blue channels (RGB) must be specified for each pixel, and so the pixel value is actually a vector of three numbers ranging from 0 to 255.\n",
    "\n",
    "One common preprocessing step in machine learning is to center and standardize your dataset, meaning that you substract the mean of the whole numpy array from each example, and then divide each example by the standard deviation of the whole numpy array. But for picture datasets, it is simpler and more convenient and works almost as well to just divide every row of the dataset by 255 (the maximum value of a pixel channel).\n",
    "\n",
    "<!-- During the training of your model, you're going to multiply weights and add biases to some initial inputs in order to observe neuron activations. Then you backpropogate with the gradients to train the model. But, it is extremely important for each feature to have a similar range such that our gradients don't explode. You will see that more in detail later in the lectures. !--> \n",
    "\n",
    "Let's standardize our dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_set_x = train_set_x_flatten/255.\n",
    "test_set_x = test_set_x_flatten/255."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color='blue'>\n",
    "**What you need to remember:**\n",
    "\n",
    "Common steps for pre-processing a new dataset are:\n",
    "- Figure out the dimensions and shapes of the problem (m_train, m_test, num_px, ...)\n",
    "- Reshape the datasets such that each example is now a vector of size (num_px \\* num_px \\* 3, 1)\n",
    "- \"Standardize\" the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3 - General Architecture of the learning algorithm ##\n",
    "\n",
    "It's time to design a simple algorithm to distinguish cat images from non-cat images.\n",
    "\n",
    "You will build a Logistic Regression, using a Neural Network mindset. The following Figure explains why **Logistic Regression is actually a very simple Neural Network!**\n",
    "\n",
    "<img src=\"images/LogReg_kiank.png\" style=\"width:650px;height:400px;\">\n",
    "\n",
    "**Mathematical expression of the algorithm**:\n",
    "\n",
    "For one example $x^{(i)}$:\n",
    "$$z^{(i)} = w^T x^{(i)} + b \\tag{1}$$\n",
    "$$\\hat{y}^{(i)} = a^{(i)} = sigmoid(z^{(i)})\\tag{2}$$ \n",
    "$$ \\mathcal{L}(a^{(i)}, y^{(i)}) =  - y^{(i)}  \\log(a^{(i)}) - (1-y^{(i)} )  \\log(1-a^{(i)})\\tag{3}$$\n",
    "\n",
    "The cost is then computed by summing over all training examples:\n",
    "$$ J = \\frac{1}{m} \\sum_{i=1}^m \\mathcal{L}(a^{(i)}, y^{(i)})\\tag{6}$$\n",
    "\n",
    "**Key steps**:\n",
    "In this exercise, you will carry out the following steps: \n",
    "    - Initialize the parameters of the model\n",
    "    - Learn the parameters for the model by minimizing the cost  \n",
    "    - Use the learned parameters to make predictions (on the test set)\n",
    "    - Analyse the results and conclude"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4 - Building the parts of our algorithm ## \n",
    "\n",
    "The main steps for building a Neural Network are:\n",
    "1. Define the model structure (such as number of input features) \n",
    "2. Initialize the model's parameters\n",
    "3. Loop:\n",
    "    - Calculate current loss (forward propagation)\n",
    "    - Calculate current gradient (backward propagation)\n",
    "    - Update parameters (gradient descent)\n",
    "\n",
    "You often build 1-3 separately and integrate them into one function we call `model()`.\n",
    "\n",
    "### 4.1 - Helper functions\n",
    "\n",
    "**Exercise**: Using your code from \"Python Basics\", implement `sigmoid()`. As you've seen in the figure above, you need to compute $sigmoid( w^T x + b) = \\frac{1}{1 + e^{-(w^T x + b)}}$ to make predictions. Use np.exp()."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# GRADED FUNCTION: sigmoid\n",
    "\n",
    "def sigmoid(z):\n",
    "    \"\"\"\n",
    "    Compute the sigmoid of z\n",
    "\n",
    "    Arguments:\n",
    "    z -- A scalar or numpy array of any size.\n",
    "\n",
    "    Return:\n",
    "    s -- sigmoid(z)\n",
    "    \"\"\"\n",
    "\n",
    "    ### START CODE HERE ### (≈ 1 line of code)\n",
    "    s = None\n",
    "    ### END CODE HERE ###\n",
    "    \n",
    "    return s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sigmoid([0, 2]) = [ 0.5         0.88079708]\n"
     ]
    }
   ],
   "source": [
    "print (\"sigmoid([0, 2]) = \" + str(sigmoid(np.array([0,2]))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Expected Output**: \n",
    "\n",
    "<table>\n",
    "  <tr>\n",
    "    <td>**sigmoid([0, 2])**</td>\n",
    "    <td> [ 0.5         0.88079708]</td> \n",
    "  </tr>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2 - Initializing parameters\n",
    "\n",
    "**Exercise:** Implement parameter initialization in the cell below. You have to initialize w as a vector of zeros. If you don't know what numpy function to use, look up np.zeros() in the Numpy library's documentation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# GRADED FUNCTION: initialize_with_zeros\n",
    "\n",
    "def initialize_with_zeros(dim):\n",
    "    \"\"\"\n",
    "    This function creates a vector of zeros of shape (dim, 1) for w and initializes b to 0.\n",
    "    \n",
    "    Argument:\n",
    "    dim -- size of the w vector we want (or number of parameters in this case)\n",
    "    \n",
    "    Returns:\n",
    "    w -- initialized vector of shape (dim, 1)\n",
    "    b -- initialized scalar (corresponds to the bias)\n",
    "    \"\"\"\n",
    "    \n",
    "    ### START CODE HERE ### (≈ 1 line of code)\n",
    "    w = None\n",
    "    b = None\n",
    "    ### END CODE HERE ###\n",
    "\n",
    "    assert(w.shape == (dim, 1))\n",
    "    assert(isinstance(b, float) or isinstance(b, int))\n",
    "    \n",
    "    return w, b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w = [[ 0.]\n",
      " [ 0.]]\n",
      "b = 0\n"
     ]
    }
   ],
   "source": [
    "dim = 2\n",
    "w, b = initialize_with_zeros(dim)\n",
    "print (\"w = \" + str(w))\n",
    "print (\"b = \" + str(b))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Expected Output**: \n",
    "\n",
    "\n",
    "<table style=\"width:15%\">\n",
    "    <tr>\n",
    "        <td>  ** w **  </td>\n",
    "        <td> [[ 0.]\n",
    " [ 0.]] </td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>  ** b **  </td>\n",
    "        <td> 0 </td>\n",
    "    </tr>\n",
    "</table>\n",
    "\n",
    "For image inputs, w will be of shape (num_px $\\times$ num_px $\\times$ 3, 1)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.3 - Forward and Backward propagation\n",
    "\n",
    "Now that your parameters are initialized, you can do the \"forward\" and \"backward\" propagation steps for learning the parameters.\n",
    "\n",
    "**Exercise:** Implement a function `propagate()` that computes the cost function and its gradient.\n",
    "\n",
    "**Hints**:\n",
    "\n",
    "Forward Propagation:\n",
    "- You get X\n",
    "- You compute $A = \\sigma(w^T X + b) = (a^{(0)}, a^{(1)}, ..., a^{(m-1)}, a^{(m)})$\n",
    "- You calculate the cost function: $J = -\\frac{1}{m}\\sum_{i=1}^{m}y^{(i)}\\log(a^{(i)})+(1-y^{(i)})\\log(1-a^{(i)})$\n",
    "\n",
    "Here are the two formulas you will be using: \n",
    "\n",
    "$$ \\frac{\\partial J}{\\partial w} = \\frac{1}{m}X(A-Y)^T\\tag{7}$$\n",
    "$$ \\frac{\\partial J}{\\partial b} = \\frac{1}{m} \\sum_{i=1}^m (a^{(i)}-y^{(i)})\\tag{8}$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# GRADED FUNCTION: propagate\n",
    "\n",
    "def propagate(w, b, X, Y):\n",
    "    \"\"\"\n",
    "    Implement the cost function and its gradient for the propagation explained above\n",
    "\n",
    "    Arguments:\n",
    "    w -- weights, a numpy array of size (num_px * num_px * 3, 1)\n",
    "    b -- bias, a scalar\n",
    "    X -- data of size (num_px * num_px * 3, number of examples)\n",
    "    Y -- true \"label\" vector (containing 0 if non-cat, 1 if cat) of size (1, number of examples)\n",
    "\n",
    "    Return:\n",
    "    cost -- negative log-likelihood cost for logistic regression\n",
    "    dw -- gradient of the loss with respect to w, thus same shape as w\n",
    "    db -- gradient of the loss with respect to b, thus same shape as b\n",
    "    \n",
    "    Tips:\n",
    "    - Write your code step by step for the propagation. np.log(), np.dot()\n",
    "    \"\"\"\n",
    "    \n",
    "    m = X.shape[1]\n",
    "    \n",
    "    # FORWARD PROPAGATION (FROM X TO COST)\n",
    "    ### START CODE HERE ### (≈ 2 lines of code)\n",
    "    A = None            # compute activation\n",
    "    cost = None         # compute cost\n",
    "    ### END CODE HERE ###\n",
    "    \n",
    "    # BACKWARD PROPAGATION (TO FIND GRAD)\n",
    "    ### START CODE HERE ### (≈ 2 lines of code)\n",
    "    dw = None\n",
    "    db = None\n",
    "    ### END CODE HERE ###\n",
    "\n",
    "    assert(dw.shape == w.shape)\n",
    "    assert(db.dtype == float)\n",
    "    cost = np.squeeze(cost)\n",
    "    assert(cost.shape == ())\n",
    "    \n",
    "    grads = {\"dw\": dw,\n",
    "             \"db\": db}\n",
    "    \n",
    "    return grads, cost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dw = [[ 0.99993216]\n",
      " [ 1.99980262]]\n",
      "db = 0.499935230625\n",
      "cost = 6.000064773192205\n"
     ]
    }
   ],
   "source": [
    "w, b, X, Y = np.array([[1],[2]]), 2, np.array([[1,2],[3,4]]), np.array([[1,0]])\n",
    "grads, cost = propagate(w, b, X, Y)\n",
    "print (\"dw = \" + str(grads[\"dw\"]))\n",
    "print (\"db = \" + str(grads[\"db\"]))\n",
    "print (\"cost = \" + str(cost))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Expected Output**:\n",
    "\n",
    "<table style=\"width:50%\">\n",
    "    <tr>\n",
    "        <td>  ** dw **  </td>\n",
    "        <td> [[ 0.99993216]\n",
    " [ 1.99980262]]</td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>  ** db **  </td>\n",
    "        <td> 0.499935230625 </td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>  ** cost **  </td>\n",
    "        <td> 6.000064773192205</td>\n",
    "    </tr>\n",
    "\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### d) Optimization\n",
    "- You have initialized your parameters.\n",
    "- You are also able to compute a cost function and its gradient.\n",
    "- Now, you want to update the parameters using gradient descent.\n",
    "\n",
    "**Exercise:** Write down the optimization function. The goal is to learn $w$ and $b$ by minimizing the cost function $J$. For a parameter $\\theta$, the update rule is $ \\theta = \\theta - \\alpha \\text{ } d\\theta$, where $\\alpha$ is the learning rate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# GRADED FUNCTION: optimize\n",
    "\n",
    "def optimize(w, b, X, Y, num_iterations, learning_rate, print_cost = False):\n",
    "    \"\"\"\n",
    "    This function optimizes w and b by running a gradient descent algorithm\n",
    "    \n",
    "    Arguments:\n",
    "    w -- weights, a numpy array of size (num_px * num_px * 3, 1)\n",
    "    b -- bias, a scalar\n",
    "    X -- data of shape (num_px * num_px * 3, number of examples)\n",
    "    Y -- true \"label\" vector (containing 0 if non-cat, 1 if cat), of shape (1, number of examples)\n",
    "    num_iterations -- number of iterations of the optimization loop\n",
    "    learning_rate -- learning rate of the gradient descent update rule\n",
    "    print_cost -- True to print the loss every 100 steps\n",
    "    \n",
    "    Returns:\n",
    "    params -- dictionary containing the weights w and bias b\n",
    "    grads -- dictionary containing the gradients of the weights and bias with respect to the cost function\n",
    "    costs -- list of all the costs computed during the optimization, this will be used to plot the learning curve.\n",
    "    \n",
    "    Tips:\n",
    "    You basically need to write down two steps and iterate through them:\n",
    "        1) Calculate the cost and the gradient for the current parameters. Use propagate().\n",
    "        2) Update the parameters using gradient descent rule for w and b.\n",
    "    \"\"\"\n",
    "    \n",
    "    costs = []\n",
    "    \n",
    "    for i in range(num_iterations):\n",
    "        \n",
    "        \n",
    "        # Cost and gradient calculation (≈ 1-4 lines of code)\n",
    "        ### START CODE HERE ### \n",
    "        grads, cost = None\n",
    "        ### END CODE HERE ###\n",
    "        \n",
    "        # Retrieve derivatives from grads\n",
    "        dw = grads[\"dw\"]\n",
    "        db = grads[\"db\"]\n",
    "        \n",
    "        # update rule (≈ 2 lines of code)\n",
    "        ### START CODE HERE ###\n",
    "        w = None\n",
    "        b = None\n",
    "        ### END CODE HERE ###\n",
    "        \n",
    "        # Record the costs\n",
    "        if i % 100 == 0:\n",
    "            costs.append(cost)\n",
    "        \n",
    "        # Print the cost every 100 training examples\n",
    "        if print_cost and i % 100 == 0:\n",
    "            print (\"Cost after iteration %i: %f\" %(i, cost))\n",
    "    \n",
    "    params = {\"w\": w,\n",
    "              \"b\": b}\n",
    "    \n",
    "    grads = {\"dw\": dw,\n",
    "             \"db\": db}\n",
    "    \n",
    "    return params, grads, costs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w = [[ 0.1124579 ]\n",
      " [ 0.23106775]]\n",
      "b = 1.55930492484\n",
      "dw = [[ 0.90158428]\n",
      " [ 1.76250842]]\n",
      "db = 0.430462071679\n"
     ]
    }
   ],
   "source": [
    "params, grads, costs = optimize(w, b, X, Y, num_iterations= 100, learning_rate = 0.009, print_cost = False)\n",
    "\n",
    "print (\"w = \" + str(params[\"w\"]))\n",
    "print (\"b = \" + str(params[\"b\"]))\n",
    "print (\"dw = \" + str(grads[\"dw\"]))\n",
    "print (\"db = \" + str(grads[\"db\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Expected Output**: \n",
    "\n",
    "<table style=\"width:40%\">\n",
    "    <tr>\n",
    "       <td> **w** </td>\n",
    "       <td>[[ 0.1124579 ]\n",
    " [ 0.23106775]] </td>\n",
    "    </tr>\n",
    "    \n",
    "    <tr>\n",
    "       <td> **b** </td>\n",
    "       <td> 1.55930492484 </td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "       <td> **dw** </td>\n",
    "       <td> [[ 0.90158428]\n",
    " [ 1.76250842]] </td>\n",
    "    </tr>\n",
    "    <tr>\n",
    "       <td> **db** </td>\n",
    "       <td> 0.430462071679 </td>\n",
    "    </tr>\n",
    "\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Exercise:** The previous function will output the learned w and b. We are able to use w and b to predict the labels for a dataset X. Implement the `predict()` function. There is two steps to computing predictions:\n",
    "\n",
    "1. Calculate $\\hat{Y} = A = \\sigma(w^T X + b)$\n",
    "\n",
    "2. Convert the entries of a into 0 (if activation <= 0.5) or 1 (if activation > 0.5), stores the predictions in a vector `Y_prediction`. If you wish, you can use an `if`/`else` statement in a `for` loop (though there is also a way to vectorize this). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "# GRADED FUNCTION: predict\n",
    "\n",
    "def predict(w, b, X):\n",
    "    '''\n",
    "    Predict whether the label is 0 or 1 using learned logistic regression parameters (w, b)\n",
    "    \n",
    "    Arguments:\n",
    "    w -- weights, a numpy array of size (num_px * num_px * 3, 1)\n",
    "    b -- bias, a scalar\n",
    "    X -- data of size (num_px * num_px * 3, number of examples)\n",
    "    \n",
    "    Returns:\n",
    "    Y_prediction -- a numpy array (vector) containing all predictions (0/1) for the examples in X\n",
    "    '''\n",
    "    \n",
    "    m = X.shape[1]\n",
    "    Y_prediction = np.zeros((1,m))\n",
    "    w = w.reshape(X.shape[0], 1)\n",
    "    \n",
    "    # Compute vector \"A\" predicting the probabilities of a cat being present in the picture\n",
    "    ### START CODE HERE ### (≈ 1 line of code)\n",
    "    A = None\n",
    "    ### END CODE HERE ###\n",
    "\n",
    "    for i in range(A.shape[1]):\n",
    "        \n",
    "        # Convert probabilities A[0,i] to actual predictions p[0,i]\n",
    "        ### START CODE HERE ### (≈ 4 lines of code)\n",
    "        Y_prediction[0, i] = None\n",
    "        ### END CODE HERE ###\n",
    "    \n",
    "    assert(Y_prediction.shape == (1, m))\n",
    "    \n",
    "    return Y_prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predictions = [[ 1.  1.]]\n"
     ]
    }
   ],
   "source": [
    "print (\"predictions = \" + str(predict(w, b, X)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Expected Output**: \n",
    "\n",
    "<table style=\"width:30%\">\n",
    "    <tr>\n",
    "         <td>\n",
    "             **predictions**\n",
    "         </td>\n",
    "          <td>\n",
    "            [[ 1.  1.]]\n",
    "         </td>  \n",
    "   </tr>\n",
    "\n",
    "</table>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "<font color='blue'>\n",
    "**What to remember:**\n",
    "You've implemented several functions that:\n",
    "- Initialize (w,b)\n",
    "- Optimize the loss iteratively to learn parameters (w,b):\n",
    "    - computing the cost and its gradient \n",
    "    - updating the parameters using gradient descent\n",
    "- Use the learned (w,b) to predict the labels for a given set of examples"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5 - Merge all functions into a model ##\n",
    "\n",
    "You will now see how the overall model is structured by putting together all the building blocks (functions implemented in the previous parts) together, in the right order.\n",
    "\n",
    "**Exercise:** Implement the model function. Use the following notation:\n",
    "    - Y_prediction for your predictions on the test set\n",
    "    - Y_prediction_train for your predictions on the train set\n",
    "    - w, costs, grads for the outputs of optimize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "# GRADED FUNCTION: model\n",
    "\n",
    "def model(X_train, Y_train, X_test, Y_test, num_iterations = 2000, learning_rate = 0.5, print_cost = False):\n",
    "    \"\"\"\n",
    "    Builds the logistic regression model by calling the function you've implemented previously\n",
    "    \n",
    "    Arguments:\n",
    "    X_train -- training set represented by a numpy array of shape (num_px * num_px * 3, m_train)\n",
    "    Y_train -- training labels represented by a numpy array (vector) of shape (1, m_train)\n",
    "    X_test -- test set represented by a numpy array of shape (num_px * num_px * 3, m_test)\n",
    "    Y_test -- test labels represented by a numpy array (vector) of shape (1, m_test)\n",
    "    num_iterations -- hyperparameter representing the number of iterations to optimize the parameters\n",
    "    learning_rate -- hyperparameter representing the learning rate used in the update rule of optimize()\n",
    "    print_cost -- Set to true to print the cost every 100 iterations\n",
    "    \n",
    "    Returns:\n",
    "    d -- dictionary containing information about the model.\n",
    "    \"\"\"\n",
    "    \n",
    "    ### START CODE HERE ###\n",
    "    \n",
    "    # initialize parameters with zeros (≈ 1 line of code)\n",
    "    w, b = None\n",
    "\n",
    "    # Gradient descent (≈ 1 line of code)\n",
    "    parameters, grads, costs = None\n",
    "    \n",
    "    # Retrieve parameters w and b from dictionary \"parameters\"\n",
    "    w = None\n",
    "    b = None\n",
    "    \n",
    "    # Predict test/train set examples (≈ 2 lines of code)\n",
    "    Y_prediction_test = None\n",
    "    Y_prediction_train = None\n",
    "\n",
    "    ### END CODE HERE ###\n",
    "\n",
    "    # Print train/test Errors\n",
    "    print(\"train accuracy: {} %\".format(100 - np.mean(np.abs(Y_prediction_train - Y_train)) * 100))\n",
    "    print(\"test accuracy: {} %\".format(100 - np.mean(np.abs(Y_prediction_test - Y_test)) * 100))\n",
    "\n",
    "    \n",
    "    d = {\"costs\": costs,\n",
    "         \"Y_prediction_test\": Y_prediction_test, \n",
    "         \"Y_prediction_train\" : Y_prediction_train, \n",
    "         \"w\" : w, \n",
    "         \"b\" : b,\n",
    "         \"learning_rate\" : learning_rate,\n",
    "         \"num_iterations\": num_iterations}\n",
    "    \n",
    "    return d"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the following cell to train your model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train accuracy: 99.04306220095694 %\n",
      "test accuracy: 70.0 %\n"
     ]
    }
   ],
   "source": [
    "d = model(train_set_x, train_set_y, test_set_x, test_set_y, num_iterations = 2000, learning_rate = 0.005, print_cost = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Expected Output**: \n",
    "\n",
    "<table style=\"width:40%\"> \n",
    "    \n",
    "    <tr>\n",
    "        <td> **Train Accuracy**  </td> \n",
    "        <td> 99.04306220095694 % </td>\n",
    "    </tr>\n",
    "\n",
    "    <tr>\n",
    "        <td>**Test Accuracy** </td> \n",
    "        <td> 70.0 % </td>\n",
    "    </tr>\n",
    "</table> \n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "**Comment**: Training accuracy is close to 100%. This is a good sanity check: your model is working and has high enough capacity to fit the training data. Test error is 68%. It is actually not bad for this simple model, given the small dataset we used and that logistic regression is a linear classifier. But no worries, you'll build an even better classifier next week!\n",
    "\n",
    "Also, you see that the model is clearly overfitting the training data. Later in this specialization you will learn how to reduce overfitting, for example by using regularization. Using the code below (and changing the `index` variable) you can look at predictions on pictures of the test set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/ipykernel/__main__.py:4: DeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "y = 1, you predicted that it is a \"cat\" picture.\n"
     ]
    },
    {
     "data": {
      "image/png": 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zhgYDhm2nkwyY5vXTt9XVIXvsp/LeebSIvU/suKwX7JcV63o5gKgAwXijbFs1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cVkuoAxEOtnBWwdyCE96Vv018DUfkM0pqfUeWFj4uzXiAVFv5Ox8LdsFAdN2Nt1AZxiShgjZ69A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\n8FnOcpaz3KGcQfgsZznLWe5Q/hVcokhRgy2SdQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f80d996bfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Example of a picture that was wrongly classified.\n",
    "index = 1\n",
    "plt.imshow(test_set_x[:,index].reshape((num_px, num_px, 3)))\n",
    "print (\"y = \" + str(test_set_y[0,index]) + \", you predicted that it is a \\\"\" + classes[d[\"Y_prediction_test\"][0,index]].decode(\"utf-8\") +  \"\\\" picture.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's also plot the cost function and the gradients."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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4VENhIeyyizqZioiI1JWCRzUNGwYTJsDHH8ddiYiISP5S8KimY4+FDTcMfT1ERESkdhQ8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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f80b4fbd438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot learning curve (with costs)\n",
    "costs = np.squeeze(d['costs'])\n",
    "plt.plot(costs)\n",
    "plt.ylabel('cost')\n",
    "plt.xlabel('iterations (per hundreds)')\n",
    "plt.title(\"Learning rate =\" + str(d[\"learning_rate\"]))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "**Interpretation**:\n",
    "You can see the cost decreasing. It shows that the parameters are being learned. However, you see that you could train the model even more on the training set. Try to increase the number of iterations in the cell above and rerun the cells. You might see that the training set accuracy goes up, but the test set accuracy goes down. This is called overfitting. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6 - Further analysis (optional/ungraded exercise) ##\n",
    "\n",
    "Congratulations on building your first image classification model. Let's analyze it further, and examine possible choices for the learning rate $\\alpha$. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Choice of learning rate ####\n",
    "\n",
    "**Reminder**:\n",
    "In order for Gradient Descent to work you must choose the learning rate wisely. The learning rate $\\alpha$  determines how rapidly we update the parameters. If the learning rate is too large we may \"overshoot\" the optimal value. Similarly, if it is too small we will need too many iterations to converge to the best values. That's why it is crucial to use a well-tuned learning rate.\n",
    "\n",
    "Let's compare the learning curve of our model with several choices of learning rates. Run the cell below. This should take about 1 minute. Feel free also to try different values than the three we have initialized the `learning_rates` variable to contain, and see what happens. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "learning rate is: 0.01\n",
      "train accuracy: 99.52153110047847 %\n",
      "test accuracy: 68.0 %\n",
      "\n",
      "-------------------------------------------------------\n",
      "\n",
      "learning rate is: 0.001\n",
      "train accuracy: 88.99521531100478 %\n",
      "test accuracy: 64.0 %\n",
      "\n",
      "-------------------------------------------------------\n",
      "\n",
      "learning rate is: 0.0001\n",
      "train accuracy: 68.42105263157895 %\n",
      "test accuracy: 36.0 %\n",
      "\n",
      "-------------------------------------------------------\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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BLL5rMd6e3qWfdM0as5vbmjVw9dVmOu5NNzk0gMyfDyNHwpkzUMIyA6IWs27K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\ngfJVTDdDAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f80b4feb5c0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "learning_rates = [0.01, 0.001, 0.0001]\n",
    "models = {}\n",
    "for i in learning_rates:\n",
    "    print (\"learning rate is: \" + str(i))\n",
    "    models[str(i)] = model(train_set_x, train_set_y, test_set_x, test_set_y, num_iterations = 1500, learning_rate = i, print_cost = False)\n",
    "    print ('\\n' + \"-------------------------------------------------------\" + '\\n')\n",
    "\n",
    "for i in learning_rates:\n",
    "    plt.plot(np.squeeze(models[str(i)][\"costs\"]), label= str(models[str(i)][\"learning_rate\"]))\n",
    "\n",
    "plt.ylabel('cost')\n",
    "plt.xlabel('iterations')\n",
    "\n",
    "legend = plt.legend(loc='upper center', shadow=True)\n",
    "frame = legend.get_frame()\n",
    "frame.set_facecolor('0.90')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Interpretation**: \n",
    "- Different learning rates give different costs and thus different predictions results.\n",
    "- If the learning rate is too large (0.01), the cost may oscillate up and down. It may even diverge (though in this example, using 0.01 still eventually ends up at a good value for the cost). \n",
    "- A lower cost doesn't mean a better model. You have to check if there is possibly overfitting. It happens when the training accuracy is a lot higher than the test accuracy.\n",
    "- In deep learning, we usually recommend that you: \n",
    "    - Choose the learning rate that better minimizes the cost function.\n",
    "    - If your model overfits, use other techniques to reduce overfitting. (We'll talk about this in later videos.) \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 7 - Test with your own image (optional/ungraded exercise) ##\n",
    "\n",
    "Congratulations on finishing this assignment. You can use your own image and see the output of your model. To do that:\n",
    "    1. Click on \"File\" in the upper bar of this notebook, then click \"Open\" to go on your Coursera Hub.\n",
    "    2. Add your image to this Jupyter Notebook's directory, in the \"images\" folder\n",
    "    3. Change your image's name in the following code\n",
    "    4. Run the code and check if the algorithm is right (1 = cat, 0 = non-cat)!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "y = 1.0, your algorithm predicts a \"cat\" picture.\n"
     ]
    },
    {
     "data": {
      "image/png": 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mQmKAhJKmLNXIKSlmro9x3733EonpHHrnMh3DaTrjMS7f2M/YvIHv5ujNpemJ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\nxJN0CjX0QIGlrQ4HuQqKz8ehM8fZ68tgi7SsLiHbo7m8ythwit2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hfX4Rw6zy0jPDXH0n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C03sWWHeqfBn37/u1y/e5v83ja3br3H6MQoi/ceojs2AavH7r0Gzz59jKXVOpW9EE888QSy\nLSM0ypyY0IkEQkwfmKNY7eHXQFMlbK+LooqMjw/jOg7g0mwU6baqqJpCtZynv7+f68tLdDQB3a/i\nFyUCsordM2nUGvgU6E+H8Uk9dL/OTj6P7blYhgmCg+oLkt8qs7m6SbdVxadpNBsN8ASCfhW7sU3c\nF8I1fYSjPsK6QqvWIx6NEI1otFtV/FqA4QE/kvvz3RD0H90a+Ze//HFq5SY+HMKqjW15/Nl7V4nK\nSdZ6/RT8SR7ly5hCgIBsc/zwDCu7dW6urLDVVfGH0+xsOUxMHiSo5FjcdhnpS6A5ZYR2k3aliI3M\ng+tbJOQgu9tLXHz+JPVinUgogD8oEwxE8AcVZMlHs96mWmtjNCuYepLh2RMIepx6T2Fnr4aqGERV\nGbuXR+m2UEUbyWwzcCDK6naTj56L0+p4LG24BAKDdN0e+x2Lj198gtdff4vc43kOnTxOde8KxXyP\nmpeka1pMjWps7ZQZ7h8jGFMp13oUbRtPlhG1MA5Bej2TpfvXqO52GB6bwRNdBM8Dz8P1LHRRJxTy\n4XkK92/Pc/LYFJd+dImdjS08p4fn2Xz+c5/BsTrsbxRY3lxmcjrIg/0mg/E9+ofSLK+b7C0Veffd\nDzj99Dk0n47tWNQNj6XNAkmfRrWSJ53yU66XiUYSHJsbxRFMREvH1aHbajA+mmR5eR3XhlSsH9Px\nsC2bhwsPOHRsGn9IZS+/ztBEmlBCxxfU8GSBWDLG/n4ZRZL5f8h7jx/LEvPK83fNu+55/154l5Em\n0mdWZmVlVbFYYlE0EpuSKLW81BiZ1QCNnlnMomfXu8GsRj29UPcM1IAkSi1RdCqyqsjyla7SZ0ZG\nRoZ/Yd6LeN5ef+8suJrFYLgZDEB9wPcv/HBwzgGOqqtkCwnGp7P0OnuUipP0bDg6bNNybOK5IutP\n16ltdVh+9JTOmsQ/v/dDbM1nIubx7MEOT59tI0ZzVPcq+KpKUVKZjQkoss+LlRUODkfs7u2SzOi8\n8eUvMjUzRavTQhYCRCTGyylcr8/TJ8vMTSXQNYFUMkE8qnLt2ku0D1v87rd+BcvuI0Zkup02sWgM\nUfDpNNpEggSSqlOaOs7keBksG8IkejwKWDiuyz//0/fJyFH0eIz2sMP8xBQqFr6gMrv4CqnYBGa6\nwEfvfMJX3rqE59rIms7tmy84e9Jg52AZz0tiaAWQA4pjYwyHHk+fPSCWUgmEAFGOkszkaHV8avUD\nhmaSS6dUVtZ1PH+EJBuUJ0c8XO2QNNIIWopSPsKz1QGxmEYYxLl6cYFPb7+g3zlgbOoUUaPD5noX\nbyhRLpdxui3S0SjbO2u88sqr3L17g7FMhqyaJKopRCSbleV9bIZM5WPYgyjPKwf8u3/7x1jVCq7V\n5jsfPqY+HDKVjfDs6Q6zU/MoqshRtYLnw4mlkyTSURKpNH3bI1kss7vfQ9VVZMXFHPRI6hoCoMgy\n7U6LaDRGMV9AFkQs2yJTymFZFhFRRpCheVhDl+MoEZFQcInH0/Q6Dql8kurRIVOax5tvfJmnT/bI\n5A32Dyqkijk63Q6xZBQJj1p1D1VS8B2fFzt78C/NI+92tvnm1y4ROEM8SaRW2+HXf/vfUbj0FZY7\nLfIRmTeKOboHW8RVASHwOFYsEnNdFH9EtdGlbklsVp4Sif8sDZc725QUk6hXZSoFZRG+dGWGE0sx\nrr1yjmE/JFMYQ41p6DGNfCGOJLdIGxa+XUPXapRnVCazKvMlnbs314nZOk/WXCo7Q0b2iFw8RTw6\ngekOmZ2bxOtp5OemGMUnePvdFcaSKYbNbQbNHnFRwdUiHEyd43D2BO9V2lTDAp7QZ3+7TnvQwnUk\nRsMmu7UdFF2n0x2gRNIQJghcEcmHQizPqy+/yWuvX6G6sYUu6qiahiCEJJQYW8s3cJp14orK7FSB\nZm0DWXIxDAM1AvNz07z//of85P2P+N7bf0s0q+H6PcaOnWPxpeusHAocmQb1bhUjFsMMEwQRDUVR\niMXiSBEFwXexHZl4VOf4mdNsH+2Tn8yy29zhswef4gVd0jGBreVPuXK2RDwPI69HKEIsGieXy2Ba\nffaOKiTzCazQRIoJDL0evUGXRqNBPAEjp0UgWoSI2PYA1RvSrT0jkwIz6NDu9Fl9vM3je6scHlZJ\nZ9Js1u7xxS++xmI5S0yVGXZGBAMLPbT541+5zJ+9OsdLkxEy2SRda0SuNMkf/+nvEMtomLbDt//m\nuxzsr2OooMgQ1UUymTRfeuUqv/Ovvs7CzGVOnbqCgIBEhH7X4uKF01jOgOFwwHDUIx1P4ds+gqhx\n4fwF5hcSJOOwvvyI3a0XLK/cZ3vnIV7QYb+2S+DbTJaLSGJAZWeDTCrF6lqF3e0+P3znEVN5yMgm\nw16XphJDjGbxkZBFkXxKwbVqdOp1Jk5eQPY8MtE4Zm+E1RmgywL5bA5z1CGu+AiRNt3+HhNTp5gr\n6sRjURSxzhdePYc/2kMLYkyOncQchdS3Vxl220xPT6Enpum39jlqbjJWHOdXv/ENzH4HOZJHjk5x\n5Y230BIei2cW0DMGv/Nb3+DB3UdcPHOFY7OnCRCIT8+wcPYq11/9IiemzvD6y8fQwxGJQpK//uG7\noBuYjosdSijxBH1zxNkzReSgz6gzwHNcorEoPtAbOAytgO1anc2qiRxNMfQs+lYfSQpBcOl069Sb\nB8TiUfa2dtjd2mLkmfSsIZ7jEo/GGJomoStQyKXR9QiyFCWfHyPiegwGPQJrRFaR8IH/9T//Ja1u\nF7NjMRh4eIFLfxgSBDqBqBFNZNCTInry50P0L5wi/+pXX+LEsUsM7IC+WePyyTnuPGvihWnufvo5\nhW6VjN3hjevnUew2ghxw858/Qu32yKkRXMcicJp89aUJzIFH0jAYm0hxdNgglUsjy+CFHolkAt8P\nSUaTrL/YRBQ1ep0+vhcwMvuMhh6jQZOpY7PEyzN87/013rm5jhwOmc5tcvzMZUYNl7HJNLmMwd3l\nOq1gmm7QZX39JhfOLfD97+2QSpXYbYW0xSxvfuNbPF17Qa6Y5NWL89y6uwbOkLnJCW7f3eTooM/l\nN17HH/YoZ30Oqz0uXH6VkQXrGyvc/OBjSoU8sViKZExnMKhSKI7x8MF9apUNOt0hhXIOP3A42nmE\nTo1Rv015fAZV8RGEEablMD4+yxeuv8Tbb/8YP1DZ2t7mzS+dYv9oxPmTJfY7UfaO4HlHgPQ0h4FI\nLQypDmxOz5ZxR12Omm16jsR0PMrx0+cxdI+QPsVygjv3bjI1VaDnqhgxHdvcISHbiBi0HZdQkpAj\nCq5tMzFeora/S7GQJ5POYDkukiKjGxq1gzqhLyD4DtFEnO5wSDIexRn2cKtd2q0NxsZLdJw+bujy\n8PZjpko5ShMqN248Rk+mQHSZGPM52G9y9dJbdI5anLtwikCQ6fWGxJMa68/3OdxcZ3FewjIHPPx8\nn+NzCxhGyLHjU0iKjCBCKh1jt9Iglpzj+WqF/uiQd356m/GJ84xMgf6wx3blKcsrG7hegKFpCIpC\nKEjIsoDpDBAClVRcw+m3yZcyzB+bYW1jmbHxEkghSiRC76jFwsIChqQzUchiS30azTpXrqRJqCN6\ntSxD38IvjlGM6cyUsoShS22vhhLpUojFuLF8QNKPctTeRZZ8GrVVypNNTGuT0OkQBD3s3goLkw7l\nVIdypkm/s86x2RTTU0nmZxOMOitMlm2WpkVOnUkRi+xzcs5gbkzkyqUoobXF5PQYMaNB1OhQ3X9I\nPqYg+3UWJgW2n99hcaHIYFCl26uSy4nsVNYQAo9sIUOpVOR7330XjA7jUzJhWKBHiiCRYG29znRR\n4HAgo8qwt7ZLIaWgSwK+oyFKIfF0mnavTyFfAFGgUCpijnQMBZxRm2uXztHpNBA8j2hcI5vLUD2o\nEtNjjIYmfccBISSdSmObNo4XoCkGluVTrx9hDhW0hITbGxDKKtOTeY6W91BjQ9pWQMKI0zrcZ2J8\nEtXQ2KpWyWTzqLpBGMJw6NIbjVjfOIB/aYrcMj3+6i//K6++fgHBFonHQsaSNu++9y6lhWnS0Shu\nfcCwss/s9ClOzi9SSqfIZCZJSwYpr8HXr5aR6WP7IRMLC2wNQsz0MY76OiNHRNOTPFnZZqdyyOOn\nz5CUCI5locgKYijgOyCEEqEq8tnDBqu1Lle+9E3G587iqhpv/fKr/MPfvocpBzhhBsdxmZ2axXYd\n5sZPMfTjrKw8ZmJxinIhw7mTeWZmFf7Df/nP7Ag65y9eRgskLuohFwZDGj96l5KpsHj+dW7duUH3\ncIgseJRKU3z4wUdcuXCc2ckyFy6eI53OIosyMkOG9SPWlh/ghgLFqQStw+doQoRkxCeht8hldSSh\nQ+X5J+iijx9aFPNlXCfgsxt3SBgGuUKC+WMTiEoEFJGB6dBsHdFHwHJ87NAliEWR8iUC32e70SWh\nxfB8CISQ2qDNWqPOh5/v09jzMc0OimKgxw2MdJ5MNo8sugQY3PjgBoKooEo6QQiBINEZDCgWiti2\nz2GjgeeHIOoctrpMTE0gaxJjk2OcWjqJFjVo1nfoHfWYPFYgGlNodpsoUpRkLIcf+mzvb6CkRijT\nBfSZHFOLBoaqs7Ux4EVlF1mRWV5f5X//+x/zd3eq/Oi7txAsg56TRkIj1AKmzuSJTfi8dP0Mlu3j\n+yCrOls7R8SSUdb3XrDybJth1+agssHNW+8w9G1a9QHl0nHOXzmLEQvp9usMR11c38X3Q1TRQFAk\nRpaHHAlxHYeIFPLGtQu4nSbd/T0GzQbJdBZfNeiHIohx3EDh7Ol5jp1Jc//zbfJTY6RFg2w+w27T\nQVBlPF8mCDW2dnsYKZkLC2m2Gs/QswJ6co+96j6Jyav42gJb+y63bq/iejP84O3H2GGK2ze2aHll\nnj6vs9cRee+9Zb7zg1VWVw95sLrDXmWfo6aBG8isH1TwxAgDK8L+1gM6HQvfM8mkEkzM+ZSnQqTA\n5cKlMyA6qAiUMgai2OXlV84S0QMG7QbLtz9ncXycsydOYHtwsH/EweYGC5dOI+ETOg5j+Qi90ZCT\ni3Ps7tdBFjisVYmIKsNun1w6jeM5DN0AEZF2YwNdVRECn9WVZezhEDUqI2khvUGHdD6NHo3RHQ6I\nKhqW7dJvdAhcyJfHEQUZz4bQF4hFBXRdw/QCopqKb3mk4klkNWDx+AJ7vQFzJ2bp9xu4foAouFQ2\nn2KPBqztN9iu2ajG7M/FvV84kKvKkFdfK/F85RkDN0HTdDiRG/HWy5Ms5XxyiSSJvI5mmnz2zrvs\nVXf5jT/8VZx4E08bcWJplvWtNWK546j5Jf7xo3VGQRklUUBUTJr7NQ4qu8RlkH2HiKoSEOIFIzx/\nhBfaSEKIa46IGCLFySKPHj8g8HwO9/d4tu7w3ZsSialp3MGQjz56m0jEw/GGhP4ISZbJqovk8mMk\nhCNalsyP3z/ik59s8D9861fJ1nb45EfvMrQdas9XcHom3/rmrxIJW2w2LFKnrpBKtOn3LJKlEucu\nz+P4A3r9Lt3+Pn/5F3+B5Hlsbq0gKhKz88cwbZePb97EdAbsbj3j9sf/jOt0UWNR0tk41mifXC6k\nWrMQJZUf/uCH9Ac98rkx1l9UaHdN6s0BteoeGxt7rD69z7A3QB30ERsbSBvbxKw+YqvB2vIzmmaf\nkenR9QKe1tvsmyPKSyfY7PSoVkMsK4/ZH3J4dIjpDojH8+gRgYlCkVanij8c8Pj2fQTTw+6PGNkW\n6XSauZljeCZ0qj3KyTKNRptsOo6My7Mnj2h3O0RUEDSPtZ0DSjMLeLaHaYIk6nz9W98iMzaGoqjU\nN7c5W1YYz0TZbUkkcnPUazV61oiJmTLRXJH9APYyk3y/WmVHyfPOZ31aXYWmOSCVj2M6HrYvEQgK\nh/UusqbzaOUxteYK5ajI7Xfv8Od/9j9y9vwVtjYeMmjViUWzhEoSWcrR61moWoH17TaumMIXNHxB\nJFcosHjyFFpEx7dADGSsYY9iIkav3aAwN8PT7QqV+iYfPHmHZv+Q6SUF2Y6zMP0WEU1kbnESF4Hd\ndhfb9VEjOoYcIyJO4/gFLp6cJDUd59bjAzJlg1wZvvPthzT2AkYdndNnfplIbJ4/+MP/iWRmiWu/\n9Md8frPJwB/HHWp0do/43d/9N5y5/DXKc1fYrthMlK8ycErkJ7/I5oHM33z7AfVRgq6fIZCO0xlN\no8avImhnQDmBlrrIxMJb1IZ5xhbfIjP2ZYZCidnFUwwGbZrDDoeNA2JGBKsjEngSo1qF5z95nwnp\niFwqzoWFacK+yf7ONksXLrLbGpFOx1BljbXnK0iSRNsc0RtaWAOHixfOs7L+mHQx97PsQtcwR0N6\nPZNIxEBRdEamiRzRaLUaTI1NUhiborJfxbM8hqM+2xub9Bp1PK2JbZmUp04h+wGxTAJRULFMl8cP\nnyAkiux36tRah+we7JPPxlDDHsPOIalkEUnJcf9e5efi3i+ctfKVr1xi0DBJ57P4DJmYeYUw6DGR\nOmJuahynHxBNZhCFkCCqMTU/Q98csHh6jtFoQLFQIpMs884nN5meOcfdRxVOnyhR262RiJiEPRMI\nCIIQUf5ZpSwIgVBAkiRcz8exTJAk3IiBEpugP9xA0zyS0TLHly6w/HwfLRYyMzdNMS6hiUPi6Tl6\nbZdMVKQ56lLfa7N4XODjWzvIRpQTuRQ79++iigLt9hFXri/xwac3GHXrFGbzXPnCL/GdD36M1n7A\nm5fSiNo4nhAhFtUxRz7dbo9YXGZucpZcNkHfPmBjc58zZy9yVB/gBB5XXz5Po7aNKnZJpwxMW8Ay\nh6hKBM81efRiAzWSZn+nyrmzx7h1+xbReJIwFFAMhXI5j6HqTE6qPN8IWJxMMB4tUk7IZOMx4pbL\nqN/ixLEZPFFlt9kmk8mSiCXYfbFJqTSJrOu4tkNInXh8nGZzE39QYX1jlVhpku2ddcKujRLKDI7q\nJGMxNFlmd7WCZEnExQRxKY7dsTBiKt1RH3voMOz5KKLIRDFPZ9gniMRxojlsP8VcfpzGYRtPFFh5\ntsJ4SeULX/s93sdo7iQAACAASURBVPvpBxz0ZJbbUQItJJ7JceRYXLlwnI8ebaIaBdxojIYYEngh\ncUNBjCRYml8gqsfodn8WnrV7AxBk/NAnlUkhWxH8gcPsfIGV5Q1qzV0yeZljM/N8fv8JA9ciEoYQ\ncXD9KH4gU63tMz01TRh4qKqG47nEowrtdptMsUwghXgICIFIqVjk5o3PuXiqyNR8CUmMY6g+zVGJ\n1b0B9eoRz4+q1F0Zt9vm8rEMGDKVp1sMkGi3HDLZJI936ozNniQYDNGjIw47CnFdZnNrk8eP73Lx\nlYvYwxaV3S1ebD3hxMIk0ycm8V2XoWvyZOU5t2/e4le+8Wvk4xpbOxXe//ATVp9uc/2Lr1KKRqlU\nDhj2PBRVwzCSvPuDHzFWKFHZ2WN7b5fHjx5z6thJNtdWuf35M8qTM1R2tjl9Nsv6zgGXrhRxrA0e\nPjxkfu4c50/PMj2doLqzzfRkiZ98dAc/FBGdDqKksNv0GMunGPYHyKqE7fkIosTBQYN0vMBeZZ/p\nY3McNasEzojQsUkkkkzPHYMAev0+ohhhcnKGaFSjddik3x8hRRQGwxaqErC7v02vZzJ1fBbNC+jb\nIWNTkwiBy4sXz8nlUtiDNqgK3rCBEomjJTIYhk42brBfa3LU9shrNuWcxIvNHfh/sVZ+4UD+ta/+\nMvGYQCC0SSdzeP4Ez9Z2EAWffDpHxE7QbHcglubA7DM9WcRzbVpHNVRRY3Vln1sPnnHh1de5t/yM\nl6+/SjIT5emLJpoewQj6eJ6LKIt4vocsSQiCRBiG+H6IJMkYuoElhbiGx17tGem4hOe0MDQPhRGN\nuo0Q+ExMpjg13UcSWmzu2kwUs4yaO6Qnx+k0IJmVWJrLUkgn8Ecu5XgaRZTpmwOuvnyee3WPjBSg\niyJG7JCrJzSOFSI8fN7G9Azu3vmQvUqVwdBjb2+X7qDJzHSR9a1V0jkNKZLl9JlzrC4/5cX6OtE4\nDHt1Br1dRiOT0yfPs7L8jEx+gufLK7zyxS+jaknGi1NoUYGZqVkunb/EQW2fXDHPhUsLtFouU+MK\nkugzbNtIvstYpoTd7RANRPrDFscXZ/FF0IDG01V67Q7bjSYj06RaOyKuNrl1/zGxTBk37JJMJmj3\nfKrDFtG+QTk9STZfxLIdisUSuWSK+l4VXVLxLRfL9yiOl/Fdh1KmSGu/TSFaJE6OVm2fXDGGEk1x\nb9cjZejc+9EPuXz9OrYsY5k9FmbjPF07pGsniOhJ1EQC0ZcIJEgVUpwo51jertJ1XU5NjtEbuKSM\nKII9IJYQSYgBzmiT1Y19Yuk8YRgiECAKAoOhQ73SIJvIcf/OIxbmjzE5Z9DotshM5MhkChiayMh8\niOlGaPdtzp9eALtDvz+EQMB1fzb/JUVEYvEorXafSEQFz6XfbhGLp9it1lmaT/Ds0QarewHjx17i\nQbXPgRJDiMeITk3Q6LrMFjJMxn0kSebxkx2G6Rx3ttpUa0cIgUF9MCIqNFANiWEwh6aMuHjhIqdO\nX8IRRBzLwdCT+L7MwrGzdIcWakTH8uC1a19kfmKeSMymdbiMEXpc+9KrvPHG6/TtFoyeceXllzm5\ndIYwhNpRld/8jV9ja2uNdDqB5ZosTk/iOCbzs5OcPHUW17P46Y/e5tJLJW7e2eLEqSTeQGJkFel0\nBvSGh4zNzPPkySqGIhAvZjncayO7LnLgEMlOISsROp0jkskUuxubDLs90pkiyUSWeqNO1+wgywKp\nuIai6dSPWiAKmIMRRlREkWE0svAcD9c0sc0R6WySTDZFOpul1zrCEQWwRXaOqvTEFJl0hmhMZ63Z\nYzgcMJYWSEZNMnoe2xFYOLmApsZoDEb0bRHfDSmlfXa3dziod+Ffmkfe7Q3QonkG/TiFsVO8++O/\n4Zdef4Mna13+4R/v8/zFNqlUlIYI8fFJgsDDNT2U0KC62wAV3vrVrxMoKhfOL+EN2tR3t9jYWKXW\n6NJzbSQtgmnZyAIEXkDo/+y1aJRQ8LH8PnJCoTsasHT2BHFdJhP3iUZ6lBMDJvNVFmcGOINHuMEh\nszOztOsviGgmqal5hEDn2U6V//bxIa16l0LiiK6zTktX6IUOLdslFk1w6Kh0CpM82j/iszuf4AYh\nP75XJX/sMqlUGlUVESSVX37rS1x56RyN3Q6VvX2ihkwQwtbGDp/fvUWrWUfRPMoTRSYnyxTyOUrF\nPD/60d8ztIasre/SbtncvvGQQcdkMOrQbg94+733+OinP2VhZoZoTKfT7nLU2Of+ox2OFbsU8yJX\nr5fo1iukZI2obnD89CIQks5qtB4/paRoFLUI1U4VUQ1Ix0Wmp4vMLnwBy59g5yBOcvo8HdvnjUvX\nkUY6mprCcwNSuRzu0GTj/grhwORga5t+o0pS0+i2GuxXatz94A619QpH27v0DytM5hexuyr7lRXG\nhB2sRpXXfv03WKt2sFwfVcnR6Eawh11i8SzucIAwaONtrxJubDE27NNsNWDY4VJCJ6xsUw46iEEL\nq9fm5NxZlp8/R5BsIkYcUQiAAEWJ4PsOUTVFeXqcB09vYqQV5OwBndEWrjfgwb2PWN29g4yIGOoo\nEQNDD9l6cQ+CDnFDIp1O0Tw8ZNDrI0sGEUVHUyP4TsD9WzfJpOJEs2mm50/iyYBssfTyWVb2avgk\nsVWVfrZMreeSTSboWjaZ/ARRI8Z64POg2cdOFfi3//O/Z+LEKZJ6jpmpInIkBaEPgsyPfvwD/u6v\n/09C0aHdayEbCiPbxREEIvhIocDs9CT/8T/+B37ww7+jPRRBSODHMnz3Ox/yF//LX0KYIZYuMAx1\nNvaaGPE00XiB/U6P8fljiEaMWDyD60ZIlSdAVnnv3ffRDY2koSLaI86evEKrm6LZz9IyZa5/+Q2W\nLl7l77//Ka+++SbRZJ6oHtDbOsIceCjRALfXZ+SEpFMqqqZy5tw5DFlAVUTqzX1CwcQ0HYq5MhFZ\np9Hpo0YNPMtBlCJkUmX6PRtJSdHr2SiKjqRqDIcmjhPgeQFmt48iuGRjcd747T/FV1Lg+qAbHDoR\nBhhomTKBY9Jo94glJQLX5LBWo923EPU4zZZJo9UlU578ubj3CwdypBG1wwr5TIEff+9t/uRP/4S6\n3aY8M09hIk8j6NIc+AiKiCcExFJ5tqp1TFFm5ItUtpvcf/iCw7bLoxdbPK88p9rY4Por5yhOn0CO\nT+JoSSLJBH4khmxoSKKEqin4jkM0olKv1ZEDHz0SIXRt4pkCjWZANBEjU4xCWCWh+STVNI2mgGW7\nHBufIxMfQ5B0Qidg4NiMKRPsdlSePLNIGlOE1gg1HceJGHRHTTxNY1Aewz15kkH6LC1hnqUzX2Rx\nbo5nK/e5dv1lUukkoWvT6rSQZAVdjxGEIbKgMTU7Rrv9s/3Eyy+9hOvAyLKQNZne0CSTn2J2vIxv\nNlEjIYqh0+73+eizGwxNi06vx+RMGUFSGQwHDM0RpVKGdi/KyqbH9HyeRr1JJjOOq4hYEQFH1jmo\nHdJt9+h3LRw35HCnwplUhql4QEKqsbHT5P7THVbWHhKRsmy+eEYubfD5R59QGC+wvbOG4DgIEZGB\nadHu9okbScZLY8SiGZLZDK2uyXgqR7fWZLw8wdrqC7rNFmvLz3HaA8qFFJ7fQ4qmePfdF9y7vYwh\nq6TzCR7fX2cq76F5NRLJLKlUDi90ySpJHt9/QjGVJT8cMOUMCXYe8UevHsMYtPH9HnfufcaFpSKt\nZh8viOB5HmEYYrkevi/h+X1+/MN/YuL4CV75lW+hp08hR05y+tQpsrqEKvk837xPvjBJEAjEDJ2I\nEtJzbB6/eMrI7CPLAYoUUjuoIkVU7j98RESLcPbSZY4aTZ48esT21hqmJZPNJyjmyjhDi9BuUYoo\ndKuHSKpCQYOEGsHzPUzLxEUH02c+Eee//qdv88H79+j3qwhCk0G7z8jy6XaPMGSD0FWRSTM7sYjn\niJxZWsKyRuxub3Pn9g0c20SWI7iui+cNkSM+YmjSax+gqQGSHIIQ4rghM9NTxOMx5ufnIJTwPZGo\nqjFeLBOLGli2zfPVVUbDLo7j8NVf/QaCINEYmNxdGZBeuMaaKfLOp5/w3VsrSPlZHjyvEnoOtumT\nMAwEOYLvCoyaz9lde4Y5tFhef44UTyHFdIqlPCg+yWSKwIywudpge6eFYqTIZMeJa1mePl5je6eC\nHjMwTRMECT1qkExmCXwBx7YwzSERNYaAj57Pc+P9m0SPamSiMvgj0kHAwPP55LMqy5WQkQeOYIEm\nUlnbJBtPIuGjIiFLKhFZ/7mw9wsHckkISGcVAvGIxcUy/+0ff8DuTpW9F3c5vtDl9Zfj7G/dZTqe\n4FeuvYIfSOxV29x9tIodGXD+mkgu3cRs1XBGMnpUxXT7bK095fCox8CDH3z0AeWFswgpHS2XxpVC\nTA9s1+LZ+lMuv/UGIzdEVYrcvbNKs15j4fgc5shlZeUJC3MFMhmdvcoWMXWM+x+0iLlpjrb26DfW\nyUSHXDyXY3dnmZlTi3QDnUEoIZcmqKsJ/uDffAN75OMOa7TuPmL/pze5dOIVvOGId97/BFyHZCrG\n8rNVYlEVWZPRNJ1f/urXmJiZJp5M0WwMyWVyfPmLX2JqbIFbHz2iedCjujsk8PI0Gx1erK5x69YD\nmkdDTl28ju8JP1sP8gQERL75zW/w+cP73HvwmMNqHdf3UTWF3/39b7JasXh0u4MSjpMtplAiMXZH\nNqX5ecbGxpB9iVQ6ix7RGJ9IkpJqTI87DIYNPCHJYWtIIpEkYSiEfhtV0ZGFCQJZ5PiJRcYKObze\nCMfs0h01OLJHPFlbYfugzmg0JCJqHLab5CcnyaZzlMsTtFstDra2UD2F3fUqiyfOsbLhYgke17/w\nFu12n1gizvjsGWIxieMlh0blM/ae36PdaiHENN546y063hBFEbAtn9/7o98mlsxwf/khhYl5/O4e\nglBnY9fCEyTCQEAQJCRRYDjo8/zZx3zz669R2+/wv/2X9zDSk6QyU6yvriI4PTLRFP1+h0dP9piY\nWMAxLUxniOVLJLNp2t0+6XScTruOqsnUm10uX36ZUBCYO36S0sQ0s9Mz5DMaH354j2PHxznaWkU3\nRExnhBL0idT3SPUGiJUXKKMOg0EfMYRjosUVaUhv/wUrjSa5YpZhawfPdHm6vE2gmgiyTBC6BAxI\nZzQePLhF4A259eltdre2EZFYmJ1DVWQ0TUOSRKQgQjyVRgoSEGiEgYSIjDkMkGWdH3z3OzxffsLj\nu3cJA5/tjXVE4Pbdz7FxQIBOp4NjD8iXivzk/VuYpk17sM65a6/xcPuAkZ5gw85iuwqN3oDayOHo\n6Ih3brzASmWoejKb2z2Ozec4OasQT3q4Xh/b98iUyty7cRPbcVBklVGjTiaW4ty5s3QbHerVBoe1\nJhfOX8QLQwJB5mC/SiKeQE8YDMwBkiwSjUVJJFKgSRTyKZZ36oSjgPlCkqgsklAiBPUayVgUYSKF\nPnGSIPCQJBiNPC5cOg/4eF6IoijYjsJwaP5c3Pv/YiHo/9crFU9hDlrYbgtJinNUr0O3wheu59jb\nHZAuZOi6HsFhi4fv/JTzX7xMIZHAtkJavR2eVPa4cLpEzKrx/qdtli5fRM8sktQljvY2yU0rXDp3\nljuPb6AEOSTJpNYY4JseVy9fYOb0OR589pRee8TUVIKUFcNp6iSmxtlrr6JF80iSwb1HLzh9/iqr\nn99kITbB5ISDyyzb/YdYnsYri8e4c7tCp9qnXBpne3OPXXOLvisyWLvDf/9nv8WpfovzZ+dpZBr8\n/X/697zy1u/zJ3/yO/T6NYxonEQ6i2u5HNXbNOo9fnzvUy5fP0UhHyMaz7P5Yp/B8TbFosKX3noJ\nPwRz4FIsLGCNDrj22lXicZXKXo/DEaiyQXWvQtTQiGkKt27cIZ0uoqoaUiixsV7BUDWmp0z+4Le/\ngd2Q2N865FD2sOIKzahKLpvG3m9iOT4kFJyuR7vdJDuT5d2P1tGjS6Qkha989WXEAOKqQ6UiIkXq\n+A5MKCWq+4c8PKrB0MJxIZI10EUJQdKIpRUiukyIxfkzx3ly5xme7ZIvjzEyW0iOw9rqCwrn8nz8\n3odIxi8xshx++ON7KEKP3/rNazQGI3Y+3uWN8zO8en4CUdN5cKvHeDrN4YsK08cuk8/mOXlljj4W\nnYMDimpAIdxifKlL5UikY6XRggGKKmPZNhFg2G+hqiF77RVOnjpDbCrNRz/9jPJ4gEWA7+nMFRfQ\n9HGGw4BWc0gYREjlJukPXHqDPg83Drh+cYqYoeK4JqbnEvgwNzeNbfaJp3OEQsj1qxeIG3H6vQHR\nSJOmmyaayXN6Yoyrgsx+vcnSsXnu7R7gOB6h4eF2esxMTKFKXR4dHjF3consRJxEJkoQmyXipojE\nAyLxGkokSnX/CEmMEwY6V1+6SqC4DNo9Br0eg76JHwboERlVzeA5LXzZRFB9fN9DBqJ6FMu2iIjQ\nbjU4rDY5e+EkiiowHA3QjRiZYh7bcdha3yAiRei3u2RzZeo9i5dOznD31mdYoUZKlMj0e2TDAN/s\no+pZkpk4rhxnf+jSVxNYvsvH9/c4MTFGeUzn5UsFTM/CswKiukGv2mYg9nj12km6fZfW0S4ZXWfU\n75Eu5en0G6QzWRqdDpZrkUgY7O9t47g++VKRaDzGYOSgxwxiRkivOUCUVRxFo3HUIW9ISIHLQiaD\n6cUZtSucnM1iuxJSILNzuE2r3yEaHyNbyJONa/TN/0db/P92v3CK3LF1zl14hVx+jHJ+krNn5nn9\n9SwffV7hkEWKhZc5P3WWkeug6xp9q4ERjRARI5SMcRR5jtUNyOezXDiXpttro0gJPN9HMassLS0R\nUzMYappOu8bjx22M8bNc/MJXsJQE+54IqSinX1+keDLHwuVZLl46w36tSyo9w27Vw0guYgdZrCDH\n0pnLbG3sEYum2N+tcFAzuPfcZXd3k2unzvC97/0TW88+R2yuU2jt8up0inOLeUIh5MrMMfxek5On\nk/zRb86TzW0xaA95vvmCw/ohkYhEGEbY3jlgba2Cohik81lGjs1+9ZD13W02KnskMtNs7DYJExrJ\nyQzFhTybR4d0LZWdDQtJTRJRXFZfbHDp5Zf4/f/uDzHtLqoUYpkm+XSc/f0qEcEgCCIIEYkXj3bZ\n3HyG63aYO5lE8U0i1UOqB4eky1M0HQgyaTq4+Fac5n6KmDZBNClyauk4oVvHC57SamxRLMjEkwHn\nr5zGajeIxXQmCpNMjJUYjDbJzmtU3A5dOWCg9/jw808JdIvv3f4Jn68+ZH+vgpGIc+3NV0mlDbJF\nHSds8vq1U2TTMTKFDMdPZfi9330NPRrBHti8+do3+Of3Vvne9x7w0+8/4dTsayzvbnOoKyjRLMcv\nnWC8PM5YYpHOWoffeX2aqcku7U4alynGxhcoxdIEgYeiyvghjM9O07Ek6u08Hzw45GCvxtWrV4hp\nBZR4nkjiFIORRGVzH8cZYFt9HE/EMlWGpokaT/HgYYXByEePGbi+ReA7hAisrLzAdX2ymQKhEODY\nFplcFjEoMFE0iKs+g96Qz+88ZNBrkS3qVOpH9FstEvEUiiiiEJBMZ4hILnORgMbaP6DJR9x/PMIo\nncK3qwh2QC5ZQtM0BHw03eH5+h3+5tv/B4mUTLN1wLHFGaJxgz//8z9HFEBUHEyvTUTQ6bdNwgCC\ncEQQDglFny+8do3Xr1/nl954A002OLZ4inQ8xUvnLhGTFULPp9NsIcsRjIhCnwEP1ocUsiNSsX1C\na4WvHS+jd44Qu21Ox5JE20OMSEDUbJGLSuhKBFuRcMNpak2fkT3gvZ/cQBQVqkdN8lOT6LLA4uw0\nGy9W6bXqNKstEATGJqao1Q/p9AesrW8hyBEmZ8fZ3lojphtMTsxgxJLUGk0CQSIVHUOVBeYyJrJz\niNMbsb1XQRBDTkzNYbbrsPMJcmuTke0iyll6Vp10Kkkhk+H4dImo7tPqthlZP99+/S9ca+X80hyp\nYgJnGKJEEjy6+z520KEfXqNhOWyvrLBYLLO1vYclwPGlk9z6+D72aMRw0KbT7nP2lfPEkllEu0M8\nPkkkFWfUtbh4epa19ReEvRBD1EgV4yhpnanZWWRBIxQkInKCRj9KpQ5H3SQPn2xQXDiJYCQIFY3C\n+CSOC8XxWXqNCqZdYWH2BE+e7pCbmWMgaCwen8dpLhONCnzlzXnKxQ4XLpxkcekyOjZf+fUv4Zke\ntc0WTtvin77/NoXSSUo5j4PKC0rTS5w/fZFcOoNvuzx+tMLFs6dYXt5A1QUioki72sLTYqwe9Pj8\n8QojIUK969IzYXu/jawW6Xo5qqaEpEp4oYqjF1jdb7BSaeKpERLjU0jJCbLFJIYQ0Dhs4wQetieT\nM3xKmT75korpgCHqlGN50mmdGw8+Y3dgchTG8SSRzEScsaksz1Y3aB91SetJhgct4pqAL/cQIgFJ\nfZJ6u0m/0UEIZNqDNu2Rg5IViZV8li5fxMLBkVpce/0KH998ytVXypRnsxhkEH2Lti8TiyXZ39pF\niqrUmiNyuRm8fogW8YgnZQRP4NGTu6SLJSYXFihlpqgP2jhCgo6k0I5GkBFYnJnkoNHhO9/+K46d\nPkutMWC3Cds7Nm9++TX+9q//imtXXsIPfRRVQRJFAlciW0jwzg8+5+zLv87ayirl8TG+9/3b5GIJ\nMinoHu4xPjXGaDBCJEQSQ9qdDrlSkmgszfLTCvV6j9mJFFFNgzAgIkkYuoJjO3Q6HZKJJN1em/Hx\nMqubu0zkFVShS6vXIx/P4Oy1mZ2fJVXKcdQdUMgXiMhDcBSGwxG6FkdWbE6fjbKz52MpM3ieSru+\niyoInDy/wOyxRYaeRei4OKZNRFLI5SfYXN2i2+oQT2QYdrtcfPllXFnF6ddBFNna3yZXKDBzbIFu\nYxc9PsVh7YC9vT1u3LrD/IklBs0aq0+esndYJ5/N4Xg22+sryLLK4tJpnDDEMMp0uy2W5uNMj6ko\npo6PiCZp2FYfVYDcRJR2e8CoekQxoZMvZDms7XP69ARiMCCijRNLqxzsNRnZQ0Ikes1Dpify9Po2\n49MTtDtdhv0hYSDg2y6ZXIpBt0P/qE02lSJEptMbkcgl2d2rMF0aQ1dF9g9aGFGfXCyFGxr8q9/6\nGoHncLTTxA+6TI/HyJdUNiouZ86cQpQE9qo1Jopl3MEASZLQNY3d3X0OD4/gX1r98F//5teQJYXL\nF09zsN+knBKoDyI8XvcYOS5zxxe4cfsG8xNjYA44fu48Tx+sIgcjBqFIXVIYG5vn04cbLC+vYmgh\nE+U5TNenOJ2g1z9AGPRYmpiiPezhyDap2BieP0QQNERP4M6ND4lpBmF/m2ajxuz8PFbgoUgKAhGC\nwEYMfBq7OxiJBNVmg1C2Oey0QYqgGFF8s09abpPSfe7fb7D1QqaYzyGIJvFoEnyB6lYH2TT55r/+\nI+5uV7n7tMq1C3GePGvx5ptfJwg8ImIMI6bRatbZ2alhWw7JjEHH1ojExpH0CGklynipwFghz7OH\nK1w8f5ZCvsjb3/+YyfI0xZjBZHIGLZJEDkQC72cwy6YLeJb0M7BNj5HNG0wWFtDCdSZzJtv7Ek8r\nfQw9jW+FpFJpMtEYrhjQ79lk9SS7T+9jdIdsPlvlta9+E0n06W5sUHlyj3g0Taw4z9aBxvPVTcYn\nY4SSS3O3gkcP4iFqUkVUJDq9Huvbz1A1FS8IkdQGtj1gNAxZXr1HNh9lf6cCgYYhC5SmJsmOz9Oo\nbiI5Xc6cX8KVJfpWi+NzJ/nHv/8BV15bQonmicUNepaPpEVQUwq+C7ceP+Gz5RYXlo7z5NFNIpkM\nr3zhNXKZMSTJ5pU3rmO2u8RzOcQgYHv3iO/849uEfo75xQVu3dxgtmTy6NldCoV50lGNuNqlnMvh\nOCH4IeWxMZLpFLbrEVc1GvUGb3zhSwxsmWxCBnuIKsnYgY+qypijIZGIgu14pOJpWo0j6nWbveoe\n02WDuek006UCdx8/QY1GGXQ7RApZ5qYKBL5FPBmn3+1Tbx6RiWd5sLzDwE/xa7/2azy4+xQsyBei\n/xd59/lrW37f9/29+tp77d7OPvv0es/tvU0vnOGIFJsoyaLkKLbiAIYDxA5iIAESBAryJLETILGR\nGHGsUFJESjTJMUmRHE6fuXPvzJ07t7dT7un97N5XXysPRs8zjyd/wwJeWL9v+XxZerLE/k6VM+cv\nIAs2hWKO4tg4sWSWhJEgGpFIxA3Wdrdo9j2yqRxef5eIWqBYmGNibI7icIHK/hZ6LMdnn14nEUth\nOiGT02M4/QadVo3J6WmSyQSmY9Pptpgan0CNxxidmKJat5GDBE6/xWAxx365R9sUcfomhckh2q7H\nxEyBnaUDcEQ8q8tBy2J2OIcm7GHZJlo0j64r1Fo1CsUSnY5DTFGxOj16/S6220fwHfBsFFUhFtU+\nD5TzAwwlSjxu0HcdYokMPdNkoJDC7HfxQoFqzeYb3/wjHi7dx0VmbHwSz7N4+GCeqKHxeGmJRl9C\n1ktEIgKWG7DfaCCGoMoSvuXjewGyFvlChyW+dJAfO3WY6alhKrVdun2bQs5itRIlmZklkU2z6QZY\nuTH6Xsjp4zPEcjq31pukDh9jsdmhLycIvQgb6xtY5gEj+TiymqTShsXNHaKigNXoIqgJSnNHiGWK\neI6GK6hYno8shgTdZc4cUkjFTQJfI5kdw1BEJElFFAR8L8CXZExJYHWhRqqUJT4KuuhSLfc+jyTt\n3CSbHOCDWzWaZpynT55gfXeBU6eOYuERj0RZerjO8r27lJttntT2EbJDTOVDWu0ar//0I4pDJQRf\n4Cc//feMDRdpVGuMTBbxRRtSk7Qabb73lae5fO40uVQEIwIvXnqWwO1w9f1PcToVNldWee0bLzI8\nNUJlb4fJEYOjhyboNbcppSIMRDXmH9xha3OXIydO8vjOHQ5P+fzinT1WvEH0zChTiQEcy8YwIhTG\nc1hOG1VWS+/B+gAAIABJREFUWbl7n99+7UUW7lxnZEpn/uE6L73yNGFjj4mpNB4y6w0dSZXJ5Qqo\nikS5sc/YkSKuYZLK5khmZAhcuu02miqgyhqOo5BNRmh1O/ihTXEgSmQgQqVbJmnpqEMRNnt1CnMl\nZD3P5KFZWj2HIAjRFY1fvv4TUjGNjF7g4YNr1Do1cjENd32Zf/6f/Am/eustBgYL1H0FQxaYGBxh\ncGwcyzRxA4kwcKk1XLKJAfBtdlbXSKWzfPzJTURSfPzZFpu7C3zvO5P8+x+/w/MvfI2YsY/Y7dNq\nVEjEZQYLY+xVD1jd3Pg8irfXRFBDQsGl0jQZG03T7zYRxc8X06xuD89ziGgRbMchk0xj923SBQlB\nSLO956OoMWJGDi2SJFNM4/oCTVWnGFeQpZC//tkblOseY2MT9Ho9dFXh5IVztLsNVlcfY2gSccXl\n6MwMM7PT7O9uoUcSdE2PldUnLDx6TESNsLu/w/buDqWkwdjIOLoqEfhVdFnixvUb9Hs1RoaztBp7\nZNIT5LMFhgYHmJ6dYe+ggm05pHNZHDdE1uO4HoxPzRArFIjIEUJJ4sGDVQ6qu6xuVnHcIqJgkFKj\nSPEo612T/coWY6UEf/u3v0ESNEZHC6xsbRLaDYaLUUw/go9MPGGQzkRpdNrEknl0RaPVcoklDTzP\nQpFVEqkUrmfj+Q6i6JPNpLHtHo4doEWTbG1VyWUH8T2HaMQgkUyQymd46+13yKSHqNVNzlw4T626\nz9rKE0bHD9FsO+yWe4yOTBOIfZbXNijkUqQiOqKosr9/QCKu0O50WNvYgv+/zZGPjo6jx3JE9WFc\ny8MLPNyuhNPeQVUUJD/A63bpazE+Xt+nG3hs9kLeW9ijJ8Tpmy77e2ucPDZHIZanNGjQbbrsrZUZ\nzI1gWw5BQuTO1h6b203a+zUUwUUWQJPhzTd+gmM5yLqB5zmocg+8Fgg6YRji+RaiaKEEJsOJGKcO\nD3N4fBo6EfaeOAwOjLO5/Jgzh47yye0DHLWAHytx5cECL3/jO2hRg3gsRScQeGfxAWO/9RXWgy6n\nTn0VSYG3Ptrk+JECB/vbpFMZHK+H6wRYfR/XtkhmZNxIgYgYsvDZJ7ihzD/7z/4L7t54QC6V5V/+\n9/8zqUiK6vY6/8N/+09JRxXSRpSf/OB1rl25hiwa/ODf/iVCT2B0bJp33nqPjt2iVm1Q2e3w1PkC\nB82QrpgkXyrQbJiIoUK/a0LoIwkSoe9yZHyE6UKJT97+kInZWSbGRigOmOiBx3bd5NH9ZYZGjlCv\n7HJsLMDpdbh/t4VgxlhZr+H2PPTQpVVpU9ksU91a5/jUIcR+E0PtsrUyT21zj255n3alRWVzn7HR\n0ww+dYytfh/NmGB7e5vN7WWufPImkhKgqxHCAE4/dZlADLn36X/gtadzvHw2yZFRhUPHJ3nj9d+g\ntTpMp5K8UFC5OJpF6tvce/c6zc0qQbdMSk/xg798k5/94m380Kc0PUqvXubv/9F3EZQK8WQfEZm3\n39tmcvgruLaNH/i0O1US8QgHW9v0+x2iMZ2R0WHm5mY5dmiamCqysnCfAT1gZXEBXTcIQgEcF0PT\nSCXiSKKP7/TY39/BtEycXpd0UidbLPHh1QVWVncoZoe5+PQFPrr/kI2Ghazq6LrOsVNH8QWB+8sr\nxEcmKJ44x1bX5Fdv3eTC5fOMjuVZXV3hb3/+cz54503u37rBGz//CR/++g1q6zvEhJC1xbuUt1ap\nV/a5e/s2P/vxj/j5z37MtSs3+c07n5LIZQkUgU8/fcD2TpeVxXkyqTiaInCws87BxjqrK+vs7x3Q\nqzfZ2d7GC330aAoNHV3RaTXaKGKIKhu8/I3vUJcEbtRtbrabfNrt0ZV1MvkkmZjBc1+5jKKpVMoV\nnj6TYGo65KDewPIlsvk0YQA7W/u0Wy02dzc+z6gR4+w2HERZQZFkVFUhmkwQiSdIZfJ0+hYIIrF4\nlF6nRS6TJxoz0DUFq9Nl88kaqhRw6swpBCnB6adfxg4+72U8++ozfDL/BFPXeP7VZxkeVllbWyOe\njDA9PoEfhgSIzMwdot5u0KlXvpB7X7qplXgshWJp/NX/9Wc89VvPo0oygwMZomGV3eoKh2yZ+7dv\nMvD1b9Fp+YiWS07v8MTsE88WMDeWiaT6HJk4QdweQZZg8cECAymF7o5PJqegJVL8+lfvktd1jj89\nxX7HxwkkRFFDDzwcN+DK430OVlucmMvSq80Tj6XohwqhExARTbr1ddK6zuDUBXYrDcxGgvxUlq21\nVY6MRdiui5x67XdobSxTr1XY0odY3bWYyNqEnoCYGUK78CxXwzjS0RN0/T4DgwOslFeIhgqXLj3F\nXnWNB+9/hqL45LOD2PYVekTJxUZ54eRxbr3zHros4AQhoiwiS1H6roPju4hanN2Wi+O5CF6E5SeP\nMIwEvX6Ldq/N8sYTjp08QiYep9+zaUoNalab4aDHG7/a5rU//ENajkG92+DK1grj6Eh1uPveJ2RP\nT+GbPmEIkSCCZ2s8WKwxOKTx/R//C5LGRUYPTWJH+5w8e5ZrNz9BS09w6FyMvOaTkHMcVJ4QjcvI\nqowYuhhGmupai2xiGMH0mMpOMXi2wMbmCqKm0XYFokaWhhnS9yfo7nc4d3iWoPWA6ZNTiKoLbpt8\nPsvq/YfMFkTOHJtktyry6VKDTnefuUyRQR0yiSyWVyavJnjnx29hFGWOnc9idhaYKp2mZ+4zNZNj\nID+KGpXp9TsUxwZxuz6//fILbDa2uf5RmcxEkoHCPkVDp94OOXriCKKjkBRT+J6JHYgsrq9RTObo\nV9uYbYfScInGygpHnz7H3toepdkBFCEgtC0IRAIhwPddcoMjVMvbRI0CmcIQPVdmZ2sRyXZp1na4\n/nGfUycv8sQBOaJj+z0unTrKUGyat69+yNWPP0XRI6TyI3RtHUUqoadNZk+cYqe6gCYZqHKWUVVk\nYGiEm59cJzdaYiqbIhqN0q/V6XcbJHJDyJLI1voCxXQGLZbiyeYCuZiB1bJJxFV+/YvXGRoYY2dv\nGdfvoqsZKpZNo+5z7sIcb/74h5RGZui165iiwsu/8x9z/NRRhCDENQWyY6dZ7M/jKXkG8gIziQij\noYGkQL1cI5ZI4bp1es19+o5Cq6dTHBxFFCUCp8PU1DGufHINLRElmU5Tf7BEIRtDUFzsfpdiJAtW\niB8qaJEMii3iug18r0vEEHDdDmvrTSR66CiEgUytXCGXm2TryW3qjSb1gyxzR0voehJRF7HcKJ98\n9pjnLx5CjGqMlYZYXl7Hsx1KpSQrq7sYsRxK/Iu596X7Iw9sh/d++WuGI1FaW6uEVoz+wTZDRYe8\n3kXq9bk0dwRDjXL82DiSJDI7PUs2cEi1Djg7rPPMkSz3rv2KaEpmfqHG9FSKwDOZmSqQHRhD1Ee4\ndP4CniDT6kcRAp+4JHDtzR/y3PkCM4Pj7NzbIh5NsbS4RUTTQeohySCoIqGgEc8M0W76LD56jKEb\n3F2vIqaTlIY0EppGv9pH75bpHCwyUUzwhy/M0mttIuk60ahBq92hF0j0rR69VsidSpXmus3A0BSt\nMCBfimHENS499SxfffUbOG4LJZsnkpjgp3/2I5r9MlbfxjEdfL/P2GgJQXJQdBfbqTNZymPIMqEo\n0rH2IfSJqjKYNjFdJ5NI4Qc2shoQMTQGBopMjo4yVBxk9tRpUAw+W1qjJsm04nnmBZd3KoscfuVZ\nUqkkSipB327h6z47zQY1PcHPP9zj+QtnqB0soWZi1Lbn6TWXOXn2GcaHc8TwaDXLhIJHdnCW1MAJ\nBHWGw6e+zeq9Kt2NEHc/SdAfxOkV+fBqi7Ejv09p9BVGxy6ztv0A0ymjKSIXz4esf/aAWDSPv2fi\nbLdxXY/Kfpl6c58zFwbZqVS58tE68fQQY4kBemu7rC8v0eu2GdWL3L7+kKHMAA/uLPL6Lz/j0zsd\ntvfr1Fs9rl+9hWdXsb0+BAGhJ/D2T99gZ3EN02wwOqagKz4zw6P0++s8vvMZgpuhbbooAxnaoUuj\n3+D48VliSZWxoXGGCyPc+uwh+7tVbl+7RT47jNnzUONRXFnFI0RWRBRFpNmsEAg+haFhYukYb/zm\nFwxlRxgaLXLv/hJJRUfqdtDbbRJGGp2Qnb19Lj11nDPHo7x22SWnlYnIFYpDcd794G2sdgNF0kmI\no5w7dYGD6jquDx+8/x4Dg3nGhibYWa0ghBqRWJ7BkSksq8/y0hOisUE2aw69QOPIyRdZ2twmmh3B\nEgImDx9Fjku8/PXXOHb2adAjnDj9Gs+98gpWP8uR4y8wc/Q4QxOneO6FbyP2HT6+coVbN+7Rlh16\neysYW/McstbJb29iL9+j2d6h1bYpTeRQ4zoCKlbH4KAOs8ePcP3mNSQJmt0uy2ur6DEDRdRZerjA\n4ZlpPHpU9rcZGMxRrZfJ5RN0OjUkxWf3YA9JixOJZxEFgWanhaLKZNIZCAX6Zg/fsrj2zuto/V3U\ndpO8EUEJJW5ducdsrkgqaGA3PBA1SgMDLKyuMjw+iu25bGxv0urV8H2wzS82tfKlg7xr9pASGqIi\nIEfr9HwJkQ6mleDkyRnEoI0Q1WlikkvniUcMVubnOZ6MIG0scnxKxzU05k6eRQtlWrUG4+MBhXwS\nRdWxCQko0dqvEYvqBKELvsz77z1GVbNsbx0wOSnxX/6Tl3j5dJR/8LuXSRgKmiAj+D6yIGILGjZJ\nbD+GKCn0bI9sKorZ6hJKUVQpiqFKmLsPycVk+pV1ItYOhi5TK1exzD71RoOCVUe68x7h47uo/QDa\ni0ylVOxWl+3NMtn0FH2nx1//9Q+wIhEmLz7Lobkp0kkPVU6QK8RQ1JAg7NNqVXG6FooXMD00zb2H\nT/jf/vX/TVROELpRUukop0/NgejRM1ssPpmnXN2j0thnc3+DVrONFPr4jk9hfJY7V6+QEgLS8RSO\nKOLoWRicwybE7XUxGy26PmxbFq1QoWcUGX3qFRpNn3i8xycfXyWdkEkaJvXmBmZnEcPpMzM4iWtW\nPq8jVuuoCYOW3eXVP/4jKsE+W5XbtLsbtPs25569QNlqUbd8bFfFC0J6nTaDpSwff1KnMDbFSKqA\n3gupzi8RE/o8frRAJGJiWQ6+dBjiFpqm8p/+k39IT/CRYyqblXWqvTb//F/+KWJGRMmkGTnzFXZd\ni2RkiDDiMF4Qsc0+oqcgBwqSpvGP/9mf8MyrZ1AEiGhthjMKzc0aGVEkJ6ncfOc2a/NbmCQoN7pU\nm3V+88sP0KQ0nW6bSrVMPKVx7Owc4xNFrl+/xvyjxzxZW2DzYBsr9DEti6ihk0kn0TWN8n6N69c+\nYDApE886tPoezz77PI1ylXMzMyQ9k1bXwnEtVC3GL3/2Bt1ynyAIOHYoZDKzg+hVGBgs0W/3uXb1\nbVYeP8LuR/jqq9/j7PnLXDhznmQqwf/z5/+OJ/N3QZIRtRgffXKdTstnqDhEpjDAzvIab73+E2RH\n4ZmXXmbvoM7E+GGy+RyTY3Nc++Aeo3OnSJWG2KnUcQORSmcbBBFJ0pk+Movj9AkCCTmSxsZl4eoH\n9Nce8MrpGaaKw/jdJpWDVXKGgWM7DI+P8Lhc5YPHK0QGjnDi3GUCN2R6YhDXsXC9gJ7VJz+QJ5PI\n0Kju0Whs4fs2UVWn2zGxbY8ni8s4lkuzVmdsZJLdikl5r4fbc5BVjdHxYRrNBoIgEuCTSmQ4fGiQ\nyakUgVnn7Mlj+H6I3QlISTLFiE5UcjmoOCSTSSJGnK21FTLJBLlEklRUR5cE0vHYF3LvS9fsfOWr\nL3BmZpb+Xp1eo07Yi5MUMmw+qtFuV3nxW69wa2UdJXeIV87O4PWqzB06jNDp4dtN4oMejWqC2x8u\nMzU0SjqrQtijZUlEM8N4BFS29oi4NrGxUUy3hxHL8Wihhhlo7B60KHdrHOz2UaI5ymacX93Y4v5S\nF0MRSaUSn2+GPVilurPDkfOnaZsma3sNNjYsRM/FoIvvNghDH8t20FWZTj+g3vbRQ4vhsWHSw1Pc\nvrfOs4MDHCsNsnfnTb759UM8evKE0YkJbnxyjzMXTrC1scyjhcckRg4jSiIT+Th2twVij+eefQ7w\nOX3mHKqs0nEdzj99mZXtbb7y0jlmpoucODJFt9th7thxFFFG1HVKw8PMzR1BklQyqQKNThvTdJma\nHSMu9tmuSZyezBN3D2hVm/gHZY4Uo9T3ypyYnSCXNQh0lSv7bcTiMK4iEksbWNtlthfvcOb8YZpV\nh6oXEo+XGB/NUt5fZyBdJLBF+r0d7t2vEDeyqLoBvoAgmowP9ZmYFRgcM+iHAqKWQ5IUREFElQwy\nmRxjQyW298ps7TSwxRB39wDdqCGEXco1aDkBo0WbEI/FjQSxbAzXDri1sclAIkdS1onqMs++eIn/\n7r/6H9ndrDBbGiJQo/zuP/hH/Ks//ykLN6/zvW+dRU7OsnbzHlHdoNqxWNrc4d3rV8CzCdyAsxOH\n0IQkS7ceMzE9hqEo1Ktt7jyaB9nCs33iMZeIL5JO5Ugkk4wNjPF4aQ09nmRsdATH76LqIm7YplKr\nkM8M0mpZ5ApFej0b33VRxABRlvjo9iaVikk+bXDv5m0y6SRdu8uR08cInB71Wp/6egvTNPloaZMn\ni3XOHEnhWSZKahKz2eLcpSNcvHyOnm/hBTad2jZ3rn9GaXyM8+fPcOHSBRw0QiFkMClT3qvycH6B\n8fESZy+e4OzFs9TbXURFIuw1WHz0kF63xwfv/JxqeYfcyBSnz53io7ffpHHQI5FRWXx0j/X1fSbH\nj1Ird3j32jXGJ8aJ+hUujwecPitx8GQbq6eTjOeYGctgmw7xTISmpfLpkyrxdIJERMLutYnIOqbZ\nJZ5MALC1s4UX+NR2K5w/d5L92gHdXp+EGsFzA4rFQXrdLhEtjqoqrK2u0zM9NEkjGjXwkInoOkld\nJ/ACspkchaFRuq5LudUimShSGC4hKgJrC1u06nukChDNVHn0cI3B8RGa9QqaZ6MJAlFNo5gt4PR7\nNOp1Nnb34P+j2fmlq5GrskokGyd/aIbnj36V2blJ5hfm6V95l6e/+XUEUecP/+CbbDTruK0ysiTh\ndCps7OwiJCTcbpfy2ia6LvJkaQNPslEkgenzMzSCNqqfxSzfJPRbPO5bFMQkxaLI7HgEXx1jeUXB\nVJJkJgQykRzvXF+hlDtBVO3R8wRcIWRvY5vBMEJkfJybH19n5thxnjk5zf17O+QSgGeho2F6AZos\nYDkeNOo8XF2g9I0X8XyHxSeLKKkkjZVHjOQz/P4fzXLnwS7OrszN5hJfe/l3yMay9Pp9dD2C1+3Q\n3anz8/l1joxG+eDD24jhdQ7NHGFjf5/BXB6730USRTb29vF6ATIeqBGUiEa1Xmc4V0CQoZDJs7P1\nhGavi67GUBSVWuOAjb0tisM6jb1l0pEiQ/kuO9UaQ+oMubpL3/axPR+r36fT8FHlCDkty9nLcxzc\n/4w6D6mls0TjOfQBG3V4hvK+Q0YXmBk7jRB6eJ6LFkaJpbrcuHGDl77+IkHo4TkylVqHWBTE0Kbn\nSWiigGoFuHYNPZOi1/dYLS8gC3UuHS8R+vu4SgTbzhGPxynODjL/7g1SUwqf3tzFj+vY+y6RiEN+\nfIZ723c5lCsSjyapWCZbpSEUNUHPaxNH5Bff/yHRyjxnLpxAjWqsPp5nWjF4+1e/4NjTF1jaXWFo\nOINvmRhaljf+5n3OvfgUsupR7reJCRqiIJNLKUi6TaXcRQtMHN/CxiWRSrF27xozkyX0vEFoqcSN\nFHc/+YzDZwcZmygiSToRVaVe7xOIUVTdotWyebwtEssPITouQhAQ1zU2NtcZn5kk6LZweh7lnX2S\nUXj8eJezL77K7Vs3eP/jOhdOGDzu1UkXsvRMn7X1bYanRtHDPs3aPIkoKHqUpScVygdPuPTyCyiK\nSGt/HSFsMjs3Q+gI3P3wHkGgcPjiGWxBoFbfxQ+rZNNn+e0/+IfomooviDTqdeamdDrdXdLps/zu\nf/Q7OJ6GZZrUugdMFUcpRtscKoAbj7G62SGWHKZdD9jZ2CRQLGKxDGoywu5ODdeyyYd95E7Awwdb\njB4dYXx2mlazSSJmkIzFsVyPVDLD/QfzJAYGiUZ1vHqNvuURiQ6TzsQwez6phMHc7DBqPMejRxts\n1HokEnFCJ8TsW1iOhWsH9L2AB6sNgk5AYcLAth0QbFJRlc16G7vsM5COM5Y1icfjHJ+bZmflCblC\nGteDcrWCZIVokvaF3PvSlVYmJiaIxmJEogbzS1tcv7XKYOkw3/z7/zlT08/Q7bts79SZyBbJZyIo\nikZxZBZPVykNjhCJptFVnaOHDpMfKZErlYgnhxElHVUy8F2LsXGDw6cGKClRFFmm0+lw8vghWq0t\n9HiU08dPs7lcpml1iA0XEHSffELFa5cRvQAl0PjMa7LrVzhzPIcfBugxkZFIj4RQQ1MlPB8k30FG\nRlI0Uqkopy9cYHhoilCKMTJSYK1q8ahjMb9+ldX1Ot0tleZqgxMD57CrbRbuP2ZiZoZ//Cf/iO+8\n9hwfvPkGr3ztEv/Lv/4Bv/+Hv8czTz/H/Pwif/y93+PKlXe4ePk8b//mLb777a/z2lcv4dtdvvnV\n51l8eJ+nzp5gdCjF5GSRg4NV+madgWKcdrfOoUPTFJJpLp25jG2naWzVMaJDVEOdS6eKqEZAPJsg\nmovzN795F9d2kGIiytoC/cf3+PRvf4Oe6lA4Msyu2cbp7XPm6Ayz2RHmpvIoKR3PD4lKIooOcmSI\nc5ee4pWXL1BIpFD/7tsPTTzN3kaLetlldPwUkhAgyXUiEZvm/mO69T0+uLaE3/NQzXlGVIn23hMK\no9MIhTS2a6FbDhExguAEUNklJcjsNE32qlWmj56gpkW4tV1j8NBpYtEcTx8/QagkCLcOmI00+c63\nXqXcKFM52EMV+5z4yln+4I9/j+HRPGdPzBHKEpF4iqySYnCkSKe5SXZsmGMTJ9HjcTLJNIfHJgkU\nBUUPmD56hIGBPFff/hU3P3gbx7OYv3uH7fk1KuV1dle2yeUT7O/vUqt22C7XWF5ep93uc/vhPWrb\ndyjbUR7vNEkYg1T2tiH0WSo3+Gh1ldffuYpjOdx4dJ+yFbLW6mNpISt7B1QbLrsdGUVN0Dx4zMfv\nvcOv3/gl6wsPGEjFWby3RDoTYaCU4WBvnbt33qdZXSGT1Hj02R1Mv8/EZI7y+g6PHt5DszzESoP1\nO3f48Z//WzTZ49SRId595y1Wnjzhh3/+IxLRDAO5CaKKTjqaojhQ5M/+99dZebKHFknSavdIRXuc\nGpG4tVHm51eqfPpEpdlVwQ9IpxUyuREUTaTX6ODV9ihoPumYDrLL6BEBq1/mvd98xPLCOl4I8Vgc\nt92jNJRjcHCQ/l4F2hYDhTyxhMHm9jb5YhFFM1h/sk/YUrh19S6mBaqRJhKN0KpW8a0Ay3ZA8dg/\nqJIpjZHIDuH6AvMPl/EJ8fBJJDL01UE+fbzOwKDGyt2HdFoWEU2l1+vQbHbwPRFJ1XC61hdy70sH\n+ebWHp4bsra0Tr/cwt4t8/0/+z5v/er7/Ol//U9ZmN9kYa+HLaX56OptXD/gRz9+g8LYJOWDDged\ngLmjh1hb3WH+8QJ6JEalWabT6eGYIQQWeiQKXoXao3fQrBqeHXLQXKdUyKLYVTYe/pjq9ocsL75P\nZfUele0NogmZw8dm2dqpsry9hmP3yAwKVGq7BNLnkyKK10XHRQw8RFlEi0ZAEoAASdMxokl++IsP\ncRyZym6VvtmjbqQYGIky/2iBQePzC+3r68vk8xlS2TyBG7K2vIYWTTAxfRpZizMyPU3KGGBodBrb\n8Tk42GNweAI5EuW1b3+L/UqTthmAnmZpdZV4IkEqY/DgwSM8L/y7hYcmQ8PDePjkYglmJqcYKY2x\n9Nku2SDB1V9cobJuEE8beE6Zs8+fo636KGocy3SQRI1CNEJGFxkZUXjmha+y+FBmb9UBX+S9N69w\n7/2rtBstfF8kgUR7cZ7q6jLvvX+H658+JBbp4DkNQsfDI8SyeoxPjjE0PIQUKChCAkEZoG/D5u4S\nsVjA6ePn6NQ8ZibnqLXaTE7P8eGN9xFiCnuPHjOQi6MZDvGkwNe/NkRQXeL02DjhxibB8gpqq48i\nSOyuraJsr7P4N3/J0Vad50d6TByR+ORBnXvLfeKJLKbVx9JkOqFHKIrs7+7jtdokE3Gae2XMTgVV\ncokn4ty/dZut+Q0UF1YfLRETorTaFeodG8WQeOG3zzN+tEjpyBSjU0fJZ3PkizlqjRbZrMHIWIZ6\nb4dQ7zB39jjb9Qr16jqbG2vcuLHEp9evc+WdW6QHDvGw0mTmqYucfO1rDBw6jCWIjE8foRyKXO9b\nvPRHf4+8FDA5PIYeL2LZAnFdwvJ7SIGD1T1AFCzqlRauG7K1u0cqmUQIAvBCsnEZFR9Fi9Dt99nZ\nXCWfNpBVlUw6gdfvAiK+GqPT76FLsLO2SETysDsVPr12FSOWYHb2ECpQKuTZWllC9TxyRpaTh7Ms\nH6zTDCY56Bk0SNJEwQu6HD42TsxQUSQJ+h6z41nGUhJqw6Hd7OLaDrmCQDoRoTQ6BgjIgkDgCrjd\nPlOFPHlVJC4oZCNZctkiqh5jeXWPnulgWw6OYzOYyZJTZQK7SbtTJhbXcH0LBI++12F1eY3mfh1L\nlql7NumBDIIs4ikyD1sNGnaIEknhuQL12g6SFKAoKsgyrXaP0A5IJJNEE1+sRv6lgzwIHdqeSX46\nQ71VZ+neCrVdk51yyMUX5liY/5QPP7jDWx/fIjEwgqqJmJ0GlfI+UmGETH6KaNpAiSuUJgbYr5WZ\nPDWBaMiIakgoh1hilngqy+VzWR5/8gNa5QUMMUrWgFykQim+w+xognxS4NRwne++lKXZ3CYdV2js\nzlNK2jx1IsTpNtCMIooSwwt8hLhIKPj4okgoBvRNG8/30FWVjZ19lg/KmFoaH4/TR6bpP7zF8p1b\nGEbUUzEvAAAgAElEQVSM4vAMq90t/uCP/5i5Zy6wXN7kxv17/MWf/wd0Q6fXa6FKMrGISi4a5cbN\nj/n0s8/Y2dkjmy1Rr9kYRpprn9zhL77/o8+zJsr7lEaGicfj2LbN4cMnaNbbNJst8gMlwkCj07Ex\nOyC4DslYkpnDM5w6dQbDNlHbDnhJitMqH7z1EYGsc+L4NIViiojs8WB+Ad+zGBjQ+Jf/6/+JLUZI\nJ0Xmb26BIzKYTZNNlZg+fIyO3SAUm8i9HodKI+SiDmpQZWVjHl+PEFhdDjbnCXyH3XKVna1lPL+B\nG/qIWpFjZ76J5WmsHXQ5/dR3ubvWpq0o6KVZzl96Dk3SUUMFyQtJakM0Dqo06y7f+d1DVB59zFen\nJ5mISPjtCoIKcSOKuLbAVFolmuyQKASs7Ve4/vARQ6NTGPEMo8NjrN5aRtXTDGZGSOt5FpbXcGyb\ni6fPUipMovgptu6t0dqukU5n6TkdWu02A9ksYaAiEPDpjXtoeo7HS0s8ubVKrx7g+RJL9+bJZwyO\nHTvH5lqFjGZQXdtEEgIsy2ZmdIQb93eYmDvO//Qv/pSoIWK7LR6WXS5eukRKVxjJJ1Cx6Hba4Elk\nC+P8H69/xJ3VMkgtBL9Gv9fGbrTBtxEFGVE0AAHP7+HYPYyYgW3ZCGGA67k0uy26VgdBBkmBSMwg\nIETVJQZKGVKFGN1uG0MRUVQVAg/T6SEoIboqkE0mCfG5++AuigS23aNW3+f1n/yIVq1MJmmztSsh\nizIZQyEaldkyQ+YuT9PzGziSiGMFKIkYPS9Pp69guyH5sSka4QCuF6XV2kPTZRRFxjF7ZDNZdrd2\neHTrLnHdwPM8Gq0OuWyB4ZFxQk8gLqsUMhkCfNLxCDFDRI9JjE9OIigaQ1OjBIpIsZQnqqlM5JNI\nkkY3mWJkahLX99io1NEGSqiey2guj6EaZJIGoighSRqVagNZkgg9h729Pbpm5wu59yWEXIDQZ+jQ\nLHOXjvNw/w5f/90XSQ3oPH68wNOXhnj+dA5VFrh96x4dyyRXiCEKOosPr9K3d7n66V1sGSaOHiKQ\no4iSimM5eI5F4KlIUgzL0wkU+O1vnySVahHVoiQyMmMT46SSeSqNHnfuzCMaUVpOyMDoUTa3l9HF\nTaamBEQ8yj2ZMJIjDDWCEBRNByD0A1Tt8+hZRVVxnYAAiWbfo9OzQApp7GxS0mVevXSSNkV8Lc9T\nL53g3/38B/zmg7fREwkOdvcIBfiLv/wrokYSZA9BFFA0kd3dLeKGgqJIuF6X4aEBAr9HEFj83u98\nC1WWcByLWCyCYzmkEnmuXP0YAg9FlGg3mziORTpp4GKjyxL12gFdyUXVBcYnD7G0uc5epYociLQ6\nIi1f5vLZc/TtEDsIOH3qPLbdpdfrYCQKXDw7jVLrYDc84tESoQeGFDD/8DaSkSQyfBgjNozXazE3\nMUqAwvT0caKhg1VeIGIHqG6ezUer0NljZ+EhRiihyRqWLRGGApYb4a2rS3jKBPmR5zCDKIEYwXFd\nAtfHiKjc/WAHe89hdbFDpdHEs/ZZXVhkeXmNaCyCKsCTSg1HF7n03Gu0rQ7Hn/4ugjpGMV8ksOo4\nXkBSS5HPZIgn4izff4Rghhw7Osd+eZ8r1z/GcUNUNKxaAz80ETMqQkalNDnGp3fvMT03i+l1KXd3\nuHv9Pi8/9w3slsjM+DiDmSxyEGG3usKNxU/IjY6xteXw8rN/gC94JFI5Qs/ioNpnf3+FfqXF4elB\nZk8c5s692/ybv/oh+Uycl589g66GIEvseH22m3VkGUy7g2l6vPjCcyjZLG6YQonm8QSJyy+eRYso\njIyNIyMRNzKIooosi3ihR4hEJKoReiG2GWJZHlEtiWX6VKotCEUUScN2bXwvIKLHCEOR8O9eepqi\n4tk9RDEEAsAlmU4iaQqWW6fdb6HrWbRYBFVRCAOFs4czyJj4qQlubpqsH7TotPs8vH8Pz5OwfY9m\nuUWnK/FgsczsoWm2Nhdx7D6ZbArb65NKGwRCyEG/haoqOKbJxuoaT9aX6XsmVr8LoUcg+vTNDoQO\nhWSK8sYGzVqVzfVt7J5Fp92hVd9Ho04icIgIGj4ysajB8bOniEUlpgsGpWwEWZUYGhpGFCL4oYok\nyRhRFdPpY/Z6pDOZL+Telw7yMPDwCXnn6mP2rBSnvvH3OPD3SUZ9BqJFHs3vMpDfpbLzhNJwFkkQ\nMV2Lh48+48xsEhyFI0cnMe0qO3tdtna3sJEQZQmREEHREUIRRcuztNqg5UfYq8NObQnXh2hykMLQ\nYZxuglK2yPjMC9jRUQTRQFf6zM2U6PoS9X6RY4deJlSjBGEfwfdJZwbxAwjCAMdxAAFZkZHEkGMz\n4zQOlpHMBpIooes5GmaXpnnAwnqZmXGbj+c3yM2c4tt/8m32qrukjTiB16eyX0cKJXyriyREaHY8\nAi8gZkQQFYkAhcrBJo7pEPom129cx4gnUA0ZVY0BEiAQ+B5jo4OUBotEFJVWo4rgOpy9fJmpqSN8\n/NYNkskhnlQPGJicpDiawrZNQi/Bg16NnmOhBCGCb6CEAn4ijhCNIsrgdRSq+w1sV2Bi9DQTQ4cx\n230Q+iCYhKGKKWms7TZoWGtI8T7L6yZmvY+1/QlGsIUeAat3wMmZMdRwj9Fsnd3VGyhBi153k4S4\nweFhA090ebzyEF9SERAIfJdQEgCR4lCOqB7DSKUIxSiTR1/m6MwwY4OjHDt7Edvz+cOvPY/mW4y9\n9BrLO1sIgosjmiQSJb726hmSrs3i4x1GiyM8WrpHtbrL2MwI9V4FfLAEl9hwip7b5dbNh2ipFF7c\nRcmDmWxQl9qYlkmv1UbAZfbsIe7uP+SDx+/SGzW5eu8jfE2g5bUYOz5GqLrIgUy33mXp4UPEQKN1\nsEsup3Hx8kVmsjF+/W/+G+zVee7d3+b8a88THZ3lyt0dghBCUePE6ADfGM7xvbNzvDg8zOUxi7hq\n88H1Ta7crmEKBj25iBzNIitROj2T8t4+kVgaOQgJBImzZy6iawbxuIbZ69Pu9vA9icAPiekRYjLY\ndpNUJgOhhR8oBL6CqqhkM1k0JaRv9ZEDHzkqYfcdxIiBH9oMjc8iagmG8hl8N8QXJTJKwIAQcLoY\nZaYgo4bwszsrlDtRJibH8R2baNLAlzyMAYMnWwcU0ymMZB5ZVxkuFiCEcqVKpblPIq6TScWZLA0j\nayq5fIZsPEFU1hFVCcs1cVwX07UJddAjUVoHVXTRJ7S6uL0mhUSaXscmmoxhxC381jpRs83e9iZ2\n32Pq8DR+vYVEBzWRIBBTxDSVwPOQIxpxVSGufx4dkMkkEUPnC7n3pYNcUES0IM7assn99QYffbJO\neWedlA5tO6CtjxM1BhkbcMhEIjg9l996/mnOzuaIZYbY2umxt7rP0fEk40MqJ08eRnREvI6HFtoY\nqo2ji1h+lLHZZzC7eQJBZCo/QFxKoYowv7TGc8+d5fy5i9iWgOwqRDwbv2/Sash0+zmS2QHadgdF\nVHEsD1WL0KzsI4kigijiuQGiKCIKMp4gstmoMFga5tD0GPgW1W6LeDrBoBznxWdSfHB1m6eefonZ\n41PU2z77+8tEIiF+IHD+0ll2dleIRCX63Rq9bpPNtW1qlRb5TI5us8royDCO4zFYLDI8UiJAQhRk\n9g/WsMwqvtfihRfPIQgShYECh47NMTRS5MTxI3SdHj9982/JxDW6OyscnznOTmuZYxdTeBIUjl4E\nylyemqLTL1NrHeA5XdSoiBlaeIJPZsCkfbDDcy+8xrVr77K79oBT509hhhpiYABNdtb36Lt1Xnrx\nIuWtHYayCfr9DdLDSTL5SSL654eYNS3C1PgcjqSzW9tit3bA4vwjxLDG/sab5PtdRpUCqi/jCeBI\nLq7voidjhIHGXrnM6bPPMH14husf7zB98isc9CtcffCAfjzGwpMDNEGjnojw3sM7aH2L2zff5I2/\n+Q0TJZ3RRIbRxCQ7e1sM5PPEIjFcSeb0U8/guB5JXePu9Zs0Og02954QzalMHDrCzv4moi6gpSQy\ngzG0mIoYjfHRnc84/sJxjGKcxKDI2PFRVva2GRyfoVZNsnS7Tq3i8erXXiWZj/Pu+++ws7vG1mad\nXqWGrFT57u+PYEQWiSzfZzKZIE6AJHrYQYgejSAoOlv37jPpu2S1VcaGTfJZA0VwOXziJYQwyvGp\nCQZTA3z87nUSiQxjs1MEeASiSiwaZeHREt1ml83VLTq9PoYeQRRUfMdFEEUSuRSoCkokwV6jS7/b\nRVEibO5VEWUF1xdJJBMUhkvoksrM1AyiIKJIUexuH8e2qdaayLqGIISIrsfFYwGjhk8QxgjiRZKa\nRrFoMP9oCVETUYwkT5odnHQUBkt0gw5a4NHvWohiQBAEjE6MMzE1TSqeIxlLUylXCD2fna095FBi\na3UT1/IZHR0llTOYmBqkNFQgmYthOi2yuSxDI4Pk82kQXFKxOEOlIcy+Ry4R4fBoEd/36fR6PL55\nD9E32avvUg+j3H24Sq/XY3dzC9c0kWWBIDBJJBUiMQEjoXwh9750kAeOT6Xn4mOx//j/Je+9niTL\n0/O85/hzMk96X1m+qququ9r39NjdmdmZ3VkHYLHLBQgChBMVBEUGIUi604VuhBtdUaFASAwFGUQE\nQQZAg3XCzhrMunHd0953eZNVWVnpfR5/dDG6F66xf8Mv4vl98X7v974f8LVXMiwlbKxAxU3MMtDy\nfPDYJp2IIIsCrmcjE7A2O8fth4csnb2CESnhjAKs7g4PbtxA0AR2K8c83XxGYPdQAxEPEZcIKBJr\nZ9/m7s0nfHJzA1/UKS6+gBBJUh+0GXojdE3k0aO7LM1dAblENFpEFmXsiYtn25/2OToh436DwHUQ\nEDAiUUajAa5jo0g+U7ksktunUMwj+iGtbp8r5y9y8eyA258csnj+i7z3g29T2d1AkT00Y4bzL1zn\n9//b3+CtL72J73r8yR//c0LP5k//1/+RP/j9b3Lh4ll+53e+iawIfP0bX0MQQ7761S9z7uIKibTB\nr/+DL0Og8c1v/ja+p1LIz6IqUbLZArliEc8ViJtp0ikTSZexYyqpy/P4eZcfPz3g3hOXck7g/off\n4ouf/QyaYGFGY+zsHCKHMqIqYMST+H6OM/Nr5LISXavDtTc/y+yZeR5u3WUYCqhqiOeEGMqEC9cX\nGXYGpA2T6tYTdNFB0KaYODqB7dGpN7Fth269z1gsMZYMYmKT9bOruGHI228t0T3+CMUe8+zGe4Ru\niCSJIMBQCNh5/pTpuQX2dmvMz5fIzzT54fs/xpNEMssreK7C0dEuZiZFu+fD4hJeIkE2NcO5pUU+\n8+pX0JM9jo4fIXg2s6UZNEWjOxwSCCGXz66jWglcTWDh7DLL6+fRonF6I4t0rsDYErC8gNFgQrdn\n448+zXsfez5jN6SQXWL7aJNYRqRULDBonXLpzHU0NcnGwRaxTIyLS+vY3SF/+73bCC2R1lGdfl/m\n0tUM/e4nuD/5iOCDj1n1A4LhiH6nwSe3bpMsl9nYfkzRlAjdDP1Kl+mISHdvi4gw4txihnZrh3HQ\n5aRaZ2puFk0U8EKPVDLKyBoRjUWIxLO88aUvowhgOzZf+0ffxLUdapUqkg+6EuVf/E//M6ahMx6P\n+I3f/g1qB0fYI5/y7DxiRMcPA9pji93qIbIs0es0MDWBZDxBEEZo1etUu4dEYgHpVIPt51v8P//l\nxyiHVUqSxXQpg64qGDqEWgQ5miWUFIoplbm8Ti4bZzwZEYYhg/GIsWWzt33A2LJJJ1OsLq+wuLCM\nFEqcWzlLKpkBGSRdxHU9XCdA0w0uXrqApiuomkQymSSdTjDo9hj3u7Q7NtFEDMdzcAOfbCFH9dku\nMdGi1RO597xGxEhzsFVBFxV0QcDQJAzdQBADBCWgP+7+nbj39w7kD58/o7Zf5fyiydUzHpn0Eb2J\nx+7tU6aJ4HQH9EKVh/dr1Op1RCnEC0LURJb5uVVGo4BQ0lGNWRQxxTd+dY2j7S3CQMWjRMQsongi\nomqgaSrZ7BKW6zKQojzf36fvhISIPN2oE9GW0MIIG0+qbB2M+OjeDrFMgVa7ghiKGGacQIb9g10E\nwDAkAGRRYjwaYhgGrVaPWtPCFrOsn5sjovgEXkCv0yAVecaDrQFdfY29zee8WJS594vvsv1sh2r7\nhD/93/6cv/yr7/Gv/o9/SxjI7O4/p3K0wYPHH/PzX/yAbNYkV0gTjafRIwrdTgNB8nDdEZ1+jWw5\nwdJ6kbNXFinMZlm9uMDcwizDfptLV1bIF1JUuzU8xyKfS/Heuz9gbvYMP/joAaqeJpqZ4ulejAvr\neTbufIgfjLh98xOSZgIfkUmvT6tWp9U6YmJvUen0iOVjvHB5DkV1WTi3ioPH2PPQ9BRTpSSTicN0\nbpqobrC+tkJSN6nsdBgOLWRRZm5miWw6Q1SPMCM4vDxXwm7ukMrk2D4K6fUdvvQ753heeZfp3AyG\nJCMEApKksHL+ImJMITVTIp6J8J3vfMzerk2x9Kkmmk2aKKMB5WyE8ajNfHkaS4zSHGjc/OA5Kxfz\n/LN//E9461d+l0a/wUxpht3dQwLfQzcUDEWjVx/Qq4a8/dYf0+46rF+7zv2tJ2D6bB8+IqKLyO6I\nrCmTUCVGTsDC2jrjzindzhHH1Q2UiMJL1z6PPenwlS9c4RcfvEe71yQIQxqnbQTL4YuvvUNKSXF2\ndhXZVjl/+U2Gvs/nv7BGTJjwwuVVAn9MbmoGTVN56bXXQYyys73Hl379q9x8cIqpFAh7HaZVE9Xx\n8CyLl199my/+2u/g+z6IEpIUxw8Dur0B//S//2P+m3/5zxh54AFmIkkoSIwcm8FohB0KtPs9nNDD\n0CMIgofluniBw9rKIq+//Tla/THDfh9JlnBDBdNMcP0zr/HWO59ncX6WbCzDZBDD9DVe++wX+d6H\nFdrDY6zGNnPJLFOeT3tzn/m1s0yGAWo4IelbxF2B9LhDyrNQZBs/cJmMHQRBoJjLoygS1njCcDwC\nQeJg/5jDSoVao8bYsah3TnECGz0aQUZidmoWVTKoVo5RZInQD/D9EE2NsjC/RLmYwTBSRFJpqr0h\nlucz6LUoJuMUYzqCb2CGIZLtUMzOEYlo9DptCEQ0LQKI6KqGKut/J+79vbvsvFDOs1wMWZz1WZqJ\ns3GrjtVMMXtujbmpOE9265RKLgwEMqkYC6UpREXkxp2P6bQGHFc9/EmLREJjOPQJRmPmpkM0PWRv\nt0nflZFMBUkyccMAIXAIJY3ZpVWWlqdB9Lj5028xk1/CHrQI/A6OK/J0/yGqqVOeKpPO5/A8DV/z\nCAWVVCzF7s42M0kRy7bAD5AkAQQBIdQQ0qvcrE24spZltVDATJok4jqaNeSDzTaH5hz22MA93efr\n33iV2sCl2xrxpS+/gRmZ5nd/77f4+U/fpds/JGJCpVJHlER29w5I5aYZjm3u37/FoN9iY+sZrU6H\nWrVKrVFHVk0CXwVBYzyxuHvvffqtIw6rGwiKxUSyOTlpMV0qc3hyiBDIvPziVfbv3OTlSwl2dvfp\nH464dCVPSJaLl9ZIxXWMiMp4bDMZ7qLJMoGT5LiroiJx1K6zePUtup0ugqoSBAZB0Catx5DlOMGw\nTiAFHOwcsjg/jyeMycSTTDodAi9gYo8JXRs3FHAFBdkQCbQskhBl1GugGknyeY/CzAxCpICLgBCE\n9HsDpheXuXnvIw4rNYorZQZjmTMLGtvbx/zBH/whH938BVdWLzFfTPLk/UccN9rETYO3r87hM0SL\nzHG8cUwuucrW4Tb7lSOWzi0RKgKaaOI7Es+f3uX06B7Pnp7ys4++w4tfuMBYnZDNzPDs/j5T5hT3\nbz1CIUH/qMHRVgVJjiNHYmiqgRpV+P4P3uXpwyecHDaIpXOIus+Fi+eoHXRQhE/f5IUL58jEDPZr\nj6k3xiwsLhNKXW7dPKK0sAZ6lJ/dvsfymTnuPN3j3vY2WUMllGF7p87czDJSIDD0JkzNRPDCGvuH\npwzGA7rtNo16i6P9YzpjF9uRafRG9EZjZDECzghdDClNz9Osdbh47QqFxQWKc1NMFECQ6ZxuoqoG\nhlkgasrk5pcJBJWIKGMND2k1HVKpHLJiIkdiHDzdIaFmSKSyxDHYeNbglc+/gRF0iEsaIy9KOVOm\n60vc3NhneWaKWuOUrQePyCVj1PefkE4ZCJrKSa2JbQdk81NYwz4HJ0fMpIpEolEcy0FTDaKxKJIG\nLWuAltBJRnV81yETT+BYE/YPKszPFpiMR8io2I5PIpFhOBkiywKhJ2KaGuNAYf7MMsWUwdM7T8nE\nAzxVIh8xyCoxbCskmtYRJZBFAcsaIKsKYRAw6A94tluFX7Y88m9++XPETZVuPeBgY8J+X6aLgT0a\nc3h0ghlzmdJVpotpcokiUkJH01SwZfSIwPlzcwjBkHw2Q6dvM7YE8ukkvnVCueRTO2lQPWkTS8Vx\nTzeRjBgRLc1//fb30bSQVMpgtpAjorYYOKf0hgOW1pZZOXeJmZlZdnfbZEqz4LuIY4dQUUnpESqV\nfWamIrRqNbwQkkaUVqfLoO3RC2RaQUhKD/Esi7hpUiil+b/+9V/zSbWHXphj3B+wbui0nj3n3FqS\nyWTMVmfC0emIw/1jDivbnDt/kVbbxlDjZFNpuqMu5fISg+4AVe4jiy7lUprTaoVzy2dZPrNCJlNC\nlKJYlkWIy6C/iRf2yEzNUqkNGfc8csUIljtGmARUKhXee/+HfP1XlgmCFEbxGh0zQ0IJCcY1Eokp\njIiBIGoc7z4iX07wfM/m7OoKQVBFNAs82jnm8ZMNpqan0VUVXJtWZZPHd+9RWjpPVPHRjQiubdPp\ndFAUBUORsMcTBCEgdGzsUMJMpjDSKcaeSzI+RySZ5rQ54rg+IAiihGKGfrtHtpDH8iwc1+Pm7dvk\nCtO8+toFsnqUdr3GSXPIpXMpfvLzjxDkHKoscvncPLVGnc5pE8Gu8NWvfYnv/OIOv/97f8Rf/9W/\nZW5qliACr3/5TQbjDpO+y//9Z/+Gjc0KV65MsX4lSb60wPnLMwwHPZ492uDRB0947fw1ut0Wqysz\nqP6ICyslSnmNyWDIrRt3mJqaJWqqyAroRppX336RzYNtvvjOOxwdHtJpdJjKFWi2dohHY9h+n9KK\nzvt3GoRGlkJuhsAysFQDY2aFza2nvLg+z0d3N7h89UWsQYVqrcFgOKDbrqPF4kydMQk1iVCKEk+B\nmTIpFhPECyazc/OoMR1fjaOZUUaeT6VRo9Pp0ul0cEY2kqwSSgGPnuwhaDL1Vp39nSOssc9ElklH\nU0wnJUJBZdAdUm9WGdguETNHtd2k3xojGjKjkY0WyighnJ7W0MKAqbV5fLdLIIwZ9gz6zphn3Sqh\nMUUpYXN355Cea1I2NbIpDUn2sS0ReywhSQqKEcVxRnSbHWKRJLqic3R8gqZ+uuwcj8Y0xn0i6Rix\nqIYaiiiKghPAsO8QiUUAcB0PXwBNj9I5HaALEQTJRzY0jlsT4nqUZFLn/p1nmJGQw6MqxXKc+kmd\ndK5APG/ieBMIPSRFxnWcTyUcz+fp9hH8soH87NosL1xdIxoVGQyGdIIowdllKpZL1wqQdYvJfoep\nvEmrPSZTzCJJIoocYWVtiY3n99EjAaISIzR0IqaPYQTsbjSoHbS5sDjN6tosTr9FJhPlB+/+jDuP\n95DDGCtr0+BP2N+8T1QdYsSTuLZGPJ3FlQ0MTee04zGxXfSYjydqDBp1PvjpjyhnIKaH5KfL9GtN\n+orL9MwqkfQMQaPHW+9cQHZ9kjEdIxrDcQMawxGWUcKOxJlJa7xgmsjREv/hP/0lX/vKBRb0NpWD\nTXQ9ihmZJx5NceHCOW7d+QXF8gLjkUS33sKIjtAMCdAQBJHNZ1tkinFOmhV6rTqTwYDC/CqiGuPR\n7UdEIxGcSUBlt4rrBKRSBtXaiEJxhrja5LPX5qk8rnLajBGN5dh2bI639rhydpmVs1dotToIQchk\n3Ofpfhtx+iK/+OAGr57PU60dM3RMoulpTmsV5opZfvqj9ziTz7J67TK9IILkjxgOOhTyBU6OKrSa\nPdLpHJIgYjk+gqjgew6DwQAjEcPyJvhyHlkRKZUXiKSKRKI5ssUyH737fZLxKKZuYhgpDnc3CQSF\nxw8f8+r1ZRTxlKtXv8az7SrXL03Tb4/IFqfQ9ZC+G5JRVf7wH1zl5o07HO11iGkC+VKeiRQwv76O\nT4hlT5iMJrz80hXu3dvC1Kd59KxFLJ4mn0jgKz73bz7kldVX8Psj0vkEibjI+sUZ9o+eMnGOefHa\nJer1Cb/6q7/K02fPWZydxYx6EAzojhvkSjMkE2lUUWTY9Dg4fsLahSk8a8CPv3Wf9Uvr9EZV9GiE\n9skEMVPmmD7//Le/ii5Cb2Tz0/c/oV5v0asP+MJnE5zUeyycWeHjewfcurvPuStXUE2B1rDP5kmV\nx0d1nuzuo5gagmIztoak0jmOW22s0OLl117i3e9+l63t55gxFV/toMZEKqcn6OkpWp7LQM5ixEwE\nr0cQ+IhRjaEQIYiUaNoivqaDHBITJ+STKuVSmUblCCkIkUXwBJFYvE91r4Ikz1A8s8DVF89y8/3b\nnFsscDpR2DzpEnUmaLJDp9dm0AopZWfx/ID8TBFBUemMRtiOR0aNYrkukvipjbnV7YKp4wQe1thi\nLjWDIZvsVY7xEPADG9930dUImq6BKKIQoXpcZ3ktB6ICcpreqMt0ucDNW8+I6D6eD6mojGZmSebj\nhKqMNRqgIuCHPrphIAvQG1g83/klBHlxeZ3+UGDj8IS1lTQpQWBcnyBk56mGDi+dyXMuM42eitBq\nDZhbmscPPW7cuIOIgCKF2OMA1zAQJA01VNi8d4zrSsQSGoIyoNp+ymzawPF9iimFRt+hPD/D+toS\nnf3nJFMj6u2AbDIJnsXOXpVUdppQNgkEDR2L090DWod3uFTUuLRmU4yr1Ksj9po+RnKOCyuX2Nd6\nP/IAACAASURBVHhap3LcQ15dpBgToD9AFFxyuRyGrBFOPLaPK/SMDLJicNBs8nB7m3D+Kp/sDHle\nOebXrixzbsFkuiTw0Sc3uPv0hM+8+jbf++F9tnc2uXwpx/s//4SZuTU++PgmkqqDqNMfgeXILM4V\n6HSqPHzwlI9u1fnDf/JbdDsj9vfaoGmsXrzM6X6L1uEOr7ywSC6uUTuaoKprnL98kaShMRRgJqWw\nu9PltHHCudXz+HKIF9jc36zSRKdYyFKSTSKJAM3Q6I8dFFUhn9U5Od5BETQi+XlcQUaUQlQhIKpp\nxKIRECCZnSIIQkRFQVBFJMEnO5XltNMjmU7jCXFqlS2EUAQ5wpPH26SzBaZKJuH4iK29fWKpNKtL\nZ5CVkKQiYCo28XiE//PffZdoap5yOY/rNnj1xc+SS8RwBZO9Rz9lOD7lwVaVz13P0rP6tIQ0iakU\nhprAcaHRqDFVLpNN5XjvvRv4YRM9ITM7V+Roe4vX33yL/ed7+JaLEeqYZonh+JThpIMSi6EZGSrH\ndb72D/8QayIxN7dC5fkGKcnDlAQ0WSGTyGP7CvNLZ6hs7bOysI5GlMrGESsLV/nWt/6Cr//Dq3z0\n8yd87jf/iMxMkt2HG5xfXmYyaeL6Dr2+gOB0ePOagTWW6YYGHUtiIqQRRRPfcnn4vIboD3CtLoro\nYibTBF6Ubv8YJRiRlj3KWYNx75TqySmeJDI7lcWyBniBgI9AEPq8dPEcuUgEM2Fw2mlTrTfxJIGH\nzx4QeH1Od57geTZ2YCNIY+amU5ixNN9/96fMTs9j6BEkxac3OGVsjxE9nQd2lE+aE8LQ51whgj9p\n4oRRdlpd0qZKQvYZOA4zuVWq1RMmvkuqlEFUZBrdLoIQYLe6SAhoqvxpDpMEfc9Ciaj0h0MER6LV\natMZ91GjErGY9qkvXtUQJBEtGiGSjBMqCk4wJBI3qZ52cB2XYjnPccNFxcbQR4QEGJk8lucRSgKj\n0RBZkhEkif5ghKxqDC2X51sH8MsG8qVrr/DSixfZPunTHoVcvDTL0aNbjPoTErqP3jhAVgz2uz08\n26VYzuH5LtliiYd3bzO/uIAnibiejORqPPjoFmZC4ll1n/rEozrQOK54rC3PMfIdijlYKWdotbts\nbNdJ53SM2BRaJMOo12BlaQkjkSeQoxwcHuONTshIR1w4Z1Iqprizc0R3UqC8OIs9GIEdst3u8cFB\nn3piiiPPo2ppJKU2sUBFSxqUSkVUKcLWg20mrQOszDyNicix4EFhBiWdJJ+NcUGe49GdxyjxCKaZ\nQJECXr02y3HlEDsUmF9aJZ/NcPXaC5hmnFwywfq5C1y79ir9/h6ebdPrWRydtrh19zFSAOfXV3n2\n5DbhuM8XXl9mOidRTAgI3gBJzLDbkpHMy+yOR4iCStpMUNm5z5svX2B+/izLZ+Y5rTUAD8Hx2N3e\nQVV0vvK5F6luPGZlYQVTDdnauk86lmbYcVi7sEIsl8XVdILxEDkaIwhlfNdHMiI0+l1GboAkSnh+\ngB+IhHiIRoSDky7p2WWs0CBdKCGrMazhmMeP7nLx8ss4foejowMuvnCNj28/otceogtDzuQFPGfI\nex88J7ZyncDwGHcc7E4Pxx1SLk/xwYcfsrwgc3/b4sq1r/LoFx+yvFak0bAoZGf49//xP3Pr5kPe\n+eLn8EIbHY12r0U+b5KbShD6QyRfIz0zx4VL51m+cJZxZ4CPT76YJZNLMrE9HMclX1pB0PMc1hro\nqkpCckiaGm5gkzITjHoDRmOXQFT5/nf/kts/v8219et4osh/fvevSE6XOawNeOPNPM+3W7R7YERy\n5GI6csThvffuIakhF2dtwmDAvY0q82c/y0GlSyGjoptxrCCD5YW0OhKKoJOJRtnZrJAvn6HeUZia\nu8bG8Zih55E2TXy7gRiIjJwYqeIC1ZMqluegSyKP79xF9AImjkUiViCWnEZOJTna2UaVXC6tlhmN\n2iwUU0SjaTYPGnQnfc5dOIuRSnDv3j2m5iQisToPnxxha0kO2iFmGDDc7lPO+pTSOlvNISdNC88a\nklR9tg5PSJkFRk6XqbkZ1LiBIIS02m180aPRaJCOJcgUczzf36E9GqCYGpIqk0jGOa7VsZwBYUTA\nNOOEwacfKSGoepRADPG8gIdPtqjsNonHfGqHhyRTRaKpKM/3junV91mY1niwUWPuzAqN+pBYwgRR\nRFIU7IlLLl/CkVQsy+Xp8234ZQP557/+ezw7atLseoxti629I975fJnxUZd0LEulPaFGgJaZ4mw5\nS66cRgo1gsDDFQTGjsvA8RFDhd27j1iYzxGbKZFfPEtg5Oj4EdqDCQsLCxz1Ax493KNUzDKdkHj8\nfBcjUyZXKqGqcSJ6GnQTRwCEKLpgkVfquCI8fDzi8bHL45HJSSDx9Mkxnb5DIa+znpPQJnDgGvR0\nGVOBz54pomPjBpBL5MhmUtz44U843t9BTUfpxTJkZI1sOsJsq8XcZJvO6QMm0Rg1JckHTwY8r9nc\n3egjKiLWxOHSxet8+7/8LTOzCR49vEtpWqNeO2Lr2WOCMCQc+3z2zXf46+9+yJ/8y39BTGlhDDeY\nLmuEwQjLF3CsLjh9KhsD1i6/w4+2XO67IZVAIB5NcqNe4cUzGm5TI7AkWp06CDayIPG9b3+H5XKJ\nS2ur9Ps1dNmndlqnkMpRKhl44wbl0iJDV0SLpvGDCZlYCsfzyOcXcRAQxTixXBGbyKeaJwKpVB5J\n07n9eIvFq68yFqNInsgkEHHcAFWFpaUydtBHkVJkiovcvr2FqWlEI2Nms1BMzaHGpznYP6FcWMTy\nh/i2h+CJvPryeWQjSlaxuLexz6mjcOvgFHUcMFPWGfXq/Kv//c/xjQgJI+SF69dwvAm+57NyZYFM\nPMugV+X69VeYjHSeH2+SLeawRZW9x1tE1SiubdE4raApHRJJEdmYRzZM/vrb72HoDmZKJwh9ZPHT\npZqqQTKd4bgm8aW3XyebUvjpD35CYEYwyimKSwU2nz9G8spcuJDl8GBEEBN5aX0en5DN5xWy2R4R\nyeLZsURxOsbmnT0GyCgTGzESpdoYY41d0sUishzDVEsM2hZBqJNITzHs2Ei2QjhWGIw0dHEaTcyw\nXe9T74coYo5IbAZBzJLOLhEvTNMcaoz6Np5j0ah16dcdFK3Is0oT11UYBTK9voItJhFDi3RKRVRy\nlOdn2XiwTbmcYnpqwlHNwjDSuI6H3ba5upbF8gacDDw2H+2yfGaBXqtOKq5DoJGaLmKkYtieDb5D\ns9eEMESNR+i7Lu1uEyNu4isC5y9cpNlqMBr0MGM65y6e5+jgCJGAQqlMv9eHQGIy8YhEdazJCFNz\nmSobZNI5klEDRInp6WmePd9nfV5jMB5TbwqUpxc4Pe2SzWVwLAs9EkGUFTQtjm1LjKwez55twS8b\nyBNmhuzZi1ROTzmTKTBsNun2u6xMi0ylzvN8dx8pO4NmxMjHNbJpk8AXCELoeCIHx3WmcjN0Gw3S\nmTjxlEE0qvPT9x8gayW6gU0yGpA0o2xWA8REiWZnzMJcyIIpMXJMpqbPMxgPCUQFO1QRpBS92i7p\n+Ihea8yxmyGRW0CRQ0IUJmMI40W6RoyUlsUL+kylDfzhgDBMIAgey/EQJQyZmpkimkzhhj6P9jaR\nY6AmYvh+HCkmo9WazIxvsbQssbT2Fg8PxzTMJabSJmIizT/6zW+wvbVNIGn0Rj1qJ0eMui7epM/s\n4gVuf3KTg8o2Z5bXmFue4f2PH/LNb/w6k+4OmeiYb32wgZw8z0hapTaCjZ0qJx2H61fznOzcR2za\nCIkcg4mHrEeRJY+gVkH3Y4iCi0fI/NI0U6Ucjuvjjm1q1T6ZpMFg1ODy+gVO+xYf37jBpbUyIlWc\n4ZBa9QgxFIlEI2iqTrN7wnAccNCuoUZSiCFENInhuMujpw+5+sqrqOYMDhFc10YRBUTBQ5EVwlBE\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8q9M5vnB9lVJUwfFGSFhY/QnFjMT1+Sk6vSq5uTJzhQWOq4+J59Ok0nkmkSRnX3yDT04n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s0mRZlxcnLC6fV1Dg73iaKIlaUl7ty5gxQCpcS8fAyelcUF4jRlMs1QaYOD3QPavS5KCoqiRCsA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J3VNRFEzHKIf3gXI23TI0jdiSvv76PazWjP0kPPAbFD8Zd8WalnAt/CEEfFR0GhsoywzvAgqZ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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f80bbb35320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## START CODE HERE ## (PUT YOUR IMAGE NAME) \n",
    "my_image = \"cat_in_iran.jpg\"   # change this to the name of your image file \n",
    "## END CODE HERE ##\n",
    "\n",
    "# We preprocess the image to fit your algorithm.\n",
    "fname = \"images/\" + my_image\n",
    "image = np.array(ndimage.imread(fname, flatten=False))\n",
    "my_image = scipy.misc.imresize(image, size=(num_px,num_px)).reshape((1, num_px*num_px*3)).T\n",
    "my_predicted_image = predict(d[\"w\"], d[\"b\"], my_image)\n",
    "\n",
    "plt.imshow(image)\n",
    "print(\"y = \" + str(np.squeeze(my_predicted_image)) + \", your algorithm predicts a \\\"\" + classes[int(np.squeeze(my_predicted_image)),].decode(\"utf-8\") +  \"\\\" picture.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font color='blue'>\n",
    "**What to remember from this assignment:**\n",
    "1. Preprocessing the dataset is important.\n",
    "2. You implemented each function separately: initialize(), propagate(), optimize(). Then you built a model().\n",
    "3. Tuning the learning rate (which is an example of a \"hyperparameter\") can make a big difference to the algorithm. You will see more examples of this later in this course!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, if you'd like, we invite you to try different things on this Notebook. Make sure you submit before trying anything. Once you submit, things you can play with include:\n",
    "    - Play with the learning rate and the number of iterations\n",
    "    - Try different initialization methods and compare the results\n",
    "    - Test other preprocessings (center the data, or divide each row by its standard deviation)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bibliography:\n",
    "- http://www.wildml.com/2015/09/implementing-a-neural-network-from-scratch/\n",
    "- https://stats.stackexchange.com/questions/211436/why-do-we-normalize-images-by-subtracting-the-datasets-image-mean-and-not-the-c"
   ]
  }
 ],
 "metadata": {
  "coursera": {
   "course_slug": "neural-networks-deep-learning",
   "graded_item_id": "XaIWT",
   "launcher_item_id": "zAgPl"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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 },
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